{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2022-12-13T23:28:35.975177Z", "start_time": "2022-12-13T23:28:35.942236Z" } }, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2023-01-16T22:42:35.247800Z", "start_time": "2023-01-16T22:42:34.126408Z" } }, "outputs": [], "source": [ "# First, I have to laod different modules that I use for analyzing the data and for plotting:\n", "import sys, os, collections\n", "import pandas as pd\n", "import numpy as np\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt; plt.rcdefaults()\n", "import re\n", "from matplotlib.pyplot import figure\n", "from collections import Counter\n", "\n", "# Second, I have to load the Text Fabric app\n", "from tf.fabric import Fabric\n", "from tf.app import use" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2023-01-16T22:42:35.911020Z", "start_time": "2023-01-16T22:42:35.905401Z" }, "tags": [] }, "outputs": [], "source": [ "pd.set_option('display.max_columns', None)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2023-01-16T22:42:48.254610Z", "start_time": "2023-01-16T22:42:37.022714Z" }, "scrolled": true, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 3 µs, sys: 1 µs, total: 4 µs\n", "Wall time: 6.91 µs\n" ] }, { "data": { "text/markdown": [ "**Locating corpus resources ...**" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "app: ~/text-fabric-data/github/etcbc/bhsa/app" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "data: ~/text-fabric-data/github/etcbc/bhsa/tf/c" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "data: ~/text-fabric-data/github/CenterBLC/BHSaddons/tf/c" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "data: ~/text-fabric-data/github/etcbc/phono/tf/c" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "data: ~/text-fabric-data/github/etcbc/parallels/tf/c" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " TF: TF API 12.3.2, etcbc/bhsa/app v3, Search Reference
\n", " Data: etcbc - bhsa c, Character table, Feature docs
\n", "
Node types\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "
Name# of nodes# slots / node% coverage
book3910938.05100
chapter929459.19100
lex923346.20100
verse2321318.38100
half_verse451809.44100
sentence637276.69100
sentence_atom645256.61100
clause881214.84100
clause_atom906884.70100
phrase2532071.68100
phrase_atom2675411.59100
subphrase1138121.4238
word4265841.00100
\n", " Sets: no custom sets
\n", " Features:
\n", "
Parallel Passages\n", "
\n", "\n", "
\n", "
\n", "crossref\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "\n", "
CenterBLC/BHSaddons/tf\n", "
\n", "\n", "
\n", "
\n", "NoFinal\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_bhsa_word_order\n", "
\n", "
str
\n", "\n", " ✅ the sequence number of each word in the BHSa (1,2,3,...)\n", "\n", "
\n", "\n", "
\n", "
\n", "bol_dict_EN\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_dict_HebArm\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_dict_PT\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_dict_abc\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_dict_vc\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_fa_order\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_g_word_utf8\n", "
\n", "
str
\n", "\n", " ✅ Transliterated words without Masoretic accent markers\n", "\n", "
\n", "\n", "
\n", "
\n", "bol_lexeme_occurrences\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_monad_num\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_number.clause-atom\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_number.phrase-atom\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_number.sentence-atom\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_number_clause_atom\n", "
\n", "
int
\n", "\n", " BOL number of clause atoms (per book)\n", "\n", "
\n", "\n", "
\n", "
\n", "bol_number_phrase_atom\n", "
\n", "
int
\n", "\n", " BOL number of phrase atoms (per book)\n", "\n", "
\n", "\n", "
\n", "
\n", "bol_number_sentence_atom\n", "
\n", "
int
\n", "\n", " BOL number of sentence atoms (per book)\n", "\n", "
\n", "\n", "
\n", "
\n", "bol_qere_presence\n", "
\n", "
int
\n", "\n", " Qere information (Qere present=1, Qere absent=0)\n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_clause\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_clause_atom\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_phrase\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_phrase_atom\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_sentence\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_sentence_atom\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_sequence_number_subphrase\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "bol_vt\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "dagesh\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_cons_nonfinal_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_word_noaccent\n", "
\n", "
str
\n", "\n", " ✅ Transliterated words without Masoretic accent markers\n", "\n", "
\n", "\n", "
\n", "
\n", "g_word_utf8_noaccent\n", "
\n", "
str
\n", "\n", " ✅ Transliterated words without Masoretic accent markers\n", "\n", "
\n", "\n", "
\n", "
\n", "g_word_utf8_noaccent_nodagesh\n", "
\n", "
str
\n", "\n", " ✅ Transliterated words without Masoretic accent markers and without Dageshes\n", "\n", "
\n", "\n", "
\n", "
\n", "lex_cons\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "\n", "
BHSA = Biblia Hebraica Stuttgartensia Amstelodamensis\n", "
\n", "\n", "
\n", "
\n", "book\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "book@ll\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "chapter\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "code\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "det\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "domain\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "freq_lex\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "function\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_cons\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_cons_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_lex\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_lex_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_word\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "g_word_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "gloss\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "gn\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "label\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "language\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "lex\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "lex_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "ls\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "nametype\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "nme\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "nu\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "number\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "otype\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "pargr\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "pdp\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "pfm\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "prs\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "prs_gn\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "prs_nu\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "prs_ps\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "ps\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "qere\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "qere_trailer\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "qere_trailer_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "qere_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "rank_lex\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "rela\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "sp\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "st\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "tab\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "trailer\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "trailer_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "txt\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "typ\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "uvf\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "vbe\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "vbs\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "verse\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "voc_lex\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "voc_lex_utf8\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "vs\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "vt\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "mother\n", "
\n", "
none
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "oslots\n", "
\n", "
none
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "\n", "
Phonetic Transcriptions\n", "
\n", "\n", "
\n", "
\n", "phono\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "phono_trailer\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "\n", " Settings:
specified
  1. apiVersion: 3
  2. appName: etcbc/bhsa
  3. appPath: /Users/oliverglanz/text-fabric-data/github/etcbc/bhsa/app
  4. commit: eb1eef532de43783a548afed016937f55572bac6
  5. css: ''
  6. dataDisplay:
    • exampleSectionHtml:<code>Genesis 1:1</code> (use <a href=\"https://github.com/{org}/{repo}/blob/master/tf/{version}/book%40en.tf\" target=\"_blank\">English book names</a>)
    • excludedFeatures:
      • g_uvf_utf8
      • g_vbs
      • kq_hybrid
      • languageISO
      • g_nme
      • lex0
      • is_root
      • g_vbs_utf8
      • g_uvf
      • dist
      • root
      • suffix_person
      • g_vbe
      • dist_unit
      • suffix_number
      • distributional_parent
      • kq_hybrid_utf8
      • crossrefSET
      • instruction
      • g_prs
      • lexeme_count
      • rank_occ
      • g_pfm_utf8
      • freq_occ
      • crossrefLCS
      • functional_parent
      • g_pfm
      • g_nme_utf8
      • g_vbe_utf8
      • kind
      • g_prs_utf8
      • suffix_gender
      • mother_object_type
    • noneValues:
      • none
      • unknown
      • no value
      • NA
  7. docs:
    • docBase: {docRoot}/{repo}
    • docExt: ''
    • docPage: ''
    • docRoot: https://{org}.github.io
    • featurePage: 0_home
  8. interfaceDefaults: {}
  9. isCompatible: True
  10. local: local
  11. localDir: /Users/oliverglanz/text-fabric-data/github/etcbc/bhsa/_temp
  12. provenanceSpec:
    • corpus: BHSA = Biblia Hebraica Stuttgartensia Amstelodamensis
    • doi: 10.5281/zenodo.1007624
    • moduleSpecs:
      • :
        • backend: no value
        • corpus: Phonetic Transcriptions
        • docUrl:https://nbviewer.jupyter.org/github/etcbc/phono/blob/master/programs/phono.ipynb
        • doi: 10.5281/zenodo.1007636
        • org: etcbc
        • relative: /tf
        • repo: phono
      • :
        • backend: no value
        • corpus: Parallel Passages
        • docUrl:https://nbviewer.jupyter.org/github/etcbc/parallels/blob/master/programs/parallels.ipynb
        • doi: 10.5281/zenodo.1007642
        • org: etcbc
        • relative: /tf
        • repo: parallels
    • org: etcbc
    • relative: /tf
    • repo: bhsa
    • version: c
    • webBase: https://shebanq.ancient-data.org/hebrew
    • webHint: Show this on SHEBANQ
    • webLang: la
    • webLexId: True
    • webUrl:{webBase}/text?book=<1>&chapter=<2>&verse=<3>&version={version}&mr=m&qw=q&tp=txt_p&tr=hb&wget=v&qget=v&nget=vt
    • webUrlLex: {webBase}/word?version={version}&id=<lid>
  13. release: v1.8
  14. typeDisplay:
    • clause:
      • label: {typ} {rela}
      • style: ''
    • clause_atom:
      • hidden: True
      • label: {code}
      • level: 1
      • style: ''
    • half_verse:
      • hidden: True
      • label: {label}
      • style: ''
      • verselike: True
    • lex:
      • featuresBare: gloss
      • label: {voc_lex_utf8}
      • lexOcc: word
      • style: orig
      • template: {voc_lex_utf8}
    • phrase:
      • label: {typ} {function}
      • style: ''
    • phrase_atom:
      • hidden: True
      • label: {typ} {rela}
      • level: 1
      • style: ''
    • sentence:
      • label: {number}
      • style: ''
    • sentence_atom:
      • hidden: True
      • label: {number}
      • level: 1
      • style: ''
    • subphrase:
      • hidden: True
      • label: {number}
      • style: ''
    • word:
      • features: pdp vs vt
      • featuresBare: lex:gloss
  15. writing: hbo
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%time\n", "#BHSa2021 = use('etcbc/bhsa', version=\"2021\", mod='CenterBLC/BHSaddons/tf')\n", "BHSa4c = use('etcbc/bhsa', version=\"c\", mod='CenterBLC/BHSaddons/tf')\n", "#DSS = use('etcbc/dss', hoist=globals())" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0.18s 4 results\n" ] }, { "data": { "text/html": [ "

result 1" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

Genesis 19:2
verse
book=Genesischapter=19verse=2
sentence 6
clause Way0 NA
phrase CP Conj
וַ
phrase VP Pred
יֹּ֜אמֶר
sentence 7
clause NmCl NA
phrase InjP Intj
הִנֶּ֣ה
phrase InjP Intj
נָּא־
clause Voct NA
phrase NP Voct
אֲדֹנַ֗י
sentence 8
clause ZIm0 NA
phrase VP Pred
ס֣וּרוּ
phrase InjP Intj
נָ֠א
phrase PP Cmpl
אֶל־
בֵּ֨ית
עַבְדְּכֶ֤ם
sentence 9
clause WIm0 NA
phrase CP Conj
וְ
phrase VP Pred
לִ֨ינוּ֙
sentence 10
clause WIm0 NA
phrase CP Conj
וְ
phrase VP Pred
רַחֲצ֣וּ
phrase NP Objc
רַגְלֵיכֶ֔ם
sentence 11
clause WQt0 NA
phrase CP Conj
וְ
phrase VP Pred
הִשְׁכַּמְתֶּ֖ם
sentence 12
clause WQt0 NA
phrase CP Conj
וַ
phrase VP Pred
הְלַכְתֶּ֣ם
phrase PP Cmpl
לְ
דַרְכְּכֶ֑ם
sentence 13
clause Way0 NA
phrase CP Conj
וַ
phrase VP Pred
יֹּאמְר֣וּ
sentence 14
clause NmCl NA
phrase NegP Nega
לֹּ֔א
sentence 15
clause xYq0 NA
phrase CP Conj
כִּ֥י
phrase PP Cmpl
בָ
רְחֹ֖וב
phrase VP Pred
נָלִֽין׃
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

result 2" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

Genesis 19:2
verse
book=Genesischapter=19verse=2
sentence 6
clause Way0 NA
phrase CP Conj
וַ
phrase VP Pred
יֹּ֜אמֶר
sentence 7
clause NmCl NA
phrase InjP Intj
הִנֶּ֣ה
phrase InjP Intj
נָּא־
clause Voct NA
phrase NP Voct
אֲדֹנַ֗י
sentence 8
clause ZIm0 NA
phrase VP Pred
ס֣וּרוּ
phrase InjP Intj
נָ֠א
phrase PP Cmpl
אֶל־
בֵּ֨ית
עַבְדְּכֶ֤ם
sentence 9
clause WIm0 NA
phrase CP Conj
וְ
phrase VP Pred
לִ֨ינוּ֙
sentence 10
clause WIm0 NA
phrase CP Conj
וְ
phrase VP Pred
רַחֲצ֣וּ
phrase NP Objc
רַגְלֵיכֶ֔ם
sentence 11
clause WQt0 NA
phrase CP Conj
וְ
phrase VP Pred
הִשְׁכַּמְתֶּ֖ם
sentence 12
clause WQt0 NA
phrase CP Conj
וַ
phrase VP Pred
הְלַכְתֶּ֣ם
phrase PP Cmpl
לְ
דַרְכְּכֶ֑ם
sentence 13
clause Way0 NA
phrase CP Conj
וַ
phrase VP Pred
יֹּאמְר֣וּ
sentence 14
clause NmCl NA
phrase NegP Nega
לֹּ֔א
sentence 15
clause xYq0 NA
phrase CP Conj
כִּ֥י
phrase PP Cmpl
בָ
רְחֹ֖וב
phrase VP Pred
נָלִֽין׃
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

result 3" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

Genesis 20:2
verse
book=Genesischapter=20verse=2
sentence 4
clause WayX NA
phrase CP Conj
וַ
phrase VP Pred
יֹּ֧אמֶר
phrase PrNP Subj
אַבְרָהָ֛ם
phrase PP Cmpl
אֶל־
שָׂרָ֥ה
אִשְׁתֹּ֖ו
sentence 5
clause NmCl NA
phrase NP PreC
אֲחֹ֣תִי
phrase PPrP Subj
הִ֑וא
sentence 6
clause WayX NA
phrase CP Conj
וַ
phrase VP Pred
יִּשְׁלַ֗ח
phrase PrNP Subj
אֲבִימֶ֨לֶךְ֙
מֶ֣לֶךְ
גְּרָ֔ר
sentence 7
clause Way0 NA
phrase CP Conj
וַ
phrase VP Pred
יִּקַּ֖ח
phrase PP Objc
אֶת־
שָׂרָֽה׃
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

result 4" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

Genesis 20:2
verse
book=Genesischapter=20verse=2
sentence 4
clause WayX NA
phrase CP Conj
וַ
phrase VP Pred
יֹּ֧אמֶר
phrase PrNP Subj
אַבְרָהָ֛ם
phrase PP Cmpl
אֶל־
שָׂרָ֥ה
אִשְׁתֹּ֖ו
sentence 5
clause NmCl NA
phrase NP PreC
אֲחֹ֣תִי
phrase PPrP Subj
הִ֑וא
sentence 6
clause WayX NA
phrase CP Conj
וַ
phrase VP Pred
יִּשְׁלַ֗ח
phrase PrNP Subj
אֲבִימֶ֨לֶךְ֙
מֶ֣לֶךְ
גְּרָ֔ר
sentence 7
clause Way0 NA
phrase CP Conj
וַ
phrase VP Pred
יִּקַּ֖ח
phrase PP Objc
אֶת־
שָׂרָֽה׃
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "TotalVocab='''\n", "verse book=Genesis chapter=19|20 verse=2\n", " clause\n", " subphrase\n", "\n", "\n", "\n", "'''\n", "TotalVocab = BHSa4c.search(TotalVocab)\n", "BHSa4c.show(TotalVocab, start=1, end=10, condensed=False, colorMap={1: 'cyan'}, multiFeatures=False)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0.82s 22667 results\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
npclausephraseword
1Genesis 1:1בְּרֵאשִׁ֖ית בָּרָ֣א אֱלֹהִ֑ים אֵ֥ת הַשָּׁמַ֖יִם וְאֵ֥ת הָאָֽרֶץ׃ אֵ֥ת הַשָּׁמַ֖יִם וְאֵ֥ת הָאָֽרֶץ׃ אֵ֥ת
2Genesis 1:4וַיַּ֧רְא אֱלֹהִ֛ים אֶת־הָאֹ֖ור אֶת־הָאֹ֖ור אֶת־
3Genesis 1:5וַיִּקְרָ֨א אֱלֹהִ֤ים׀ לָאֹור֙ יֹ֔ום יֹ֔ום יֹ֔ום
4Genesis 1:5וְלַחֹ֖שֶׁךְ קָ֣רָא לָ֑יְלָה לָ֑יְלָה לָ֑יְלָה
5Genesis 1:7וַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ אֶת־הָרָקִיעַ֒ אֶת־
6Genesis 1:8וַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם שָׁמָ֑יִם שָׁמָ֑יִם
7Genesis 1:10וַיִּקְרָ֨א אֱלֹהִ֤ים׀ לַיַּבָּשָׁה֙ אֶ֔רֶץ אֶ֔רֶץ אֶ֔רֶץ
8Genesis 1:10וּלְמִקְוֵ֥ה הַמַּ֖יִם קָרָ֣א יַמִּ֑ים יַמִּ֑ים יַמִּ֑ים
9Genesis 1:11תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ֔שֶׁא עֵ֚שֶׂב עֵ֣ץ פְּרִ֞י דֶּ֔שֶׁא עֵ֚שֶׂב עֵ֣ץ פְּרִ֞י דֶּ֔שֶׁא
10Genesis 1:11מַזְרִ֣יעַ זֶ֔רַע זֶ֔רַע זֶ֔רַע
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "TotalVocab='''\n", "clause\n", " p1:phrase function=Objc\n", " w1:word\n", "\n", "p1 =: w1\n", "\n", "'''\n", "TotalVocab = BHSa4c.search(TotalVocab)\n", "BHSa4c.table(TotalVocab, start=1, end=10, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# BOL exercises\n", "## complete vocab" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "TotalVocab='''\n", "word lex* bol_dict_HebArm* bol_dict_EN* number* freq_occ* rank_occ* bol_fa_order* bol_lexeme_occurrences* bol_dict_abc* language* bol_monad_num* qere_utf8* g_word_utf8* g_lex_utf8* bol_g_word_utf8* bol_qere_presence*\n", "\n", "'''\n", "TotalVocab = BHSa4c.search(TotalVocab)\n", "BHSa4c.table(TotalVocab, start=1, end=5, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "BHSa4c.export(TotalVocab, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises', toFile='BHSa4c_BOL_vocab.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "TotalVocab=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_vocab.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "TotalVocab.head(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Getting the vocab for Hebrew-I, Hebrew-II, Hebrew-III" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab='''\n", "word lex* bol_dict_HebArm* bol_dict_EN number* g_word_noaccent* freq_occ* rank_occ* bol_fa_order* bol_dict_vc* sp* bol_lexeme_occurrences* bol_dict_abc* language* bol_monad_num* qere_utf8* g_word_utf8* g_lex_utf8* bol_g_word_utf8* bol_qere_presence*\n", "\n", "'''\n", "HebrewWordRank_BibleOL_Vocab = BHSa4c.search(HebrewWordRank_BibleOL_Vocab)\n", "BHSa4c.table(HebrewWordRank_BibleOL_Vocab, start=1, end=5, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(HebrewWordRank_BibleOL_Vocab, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises', toFile='BHSa4c_BOL_vocab_exercises_HebI-II-III.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallWords=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_vocab_exercises_HebI-II-III.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "BHSallWords.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords=BHSallWords[(BHSallWords['language1']=='Hebrew') \n", " & (BHSallWords['bol_lexeme_occurrences1']>=40)\n", " & (~BHSallWords['g_word_noaccent1'].astype(str).str.contains(\"^\\*\"))\n", " & (~BHSallWords['bol_dict_vc1'].astype(str).str.contains(\"four.*verb\"))\n", "\n", " ]\n", "BHSallHebrewWords.head() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Sequenced Selection with `nth` " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords_selection_of_sequenced2=BHSallHebrewWords.groupby('bol_dict_HebArm1').nth((0,1,2)).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "BHSallHebrewWords_selection_of_sequenced2.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Random Selection `sample` " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords_selection_of_random3=BHSallHebrewWords.groupby('bol_dict_HebArm1').sample(n=3, replace=True).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "BHSallHebrewWords_selection_of_random3.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords_selection_of_random3.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/OTST551_vocab_exercise-pool_Heb-I-II-III_vocab_selection_of_3.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Selecting only Vocab of Genesis" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallWords=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_vocab_exercises_HebI-II-III.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', enccoding='utf-16')\n", "\n", "BHSallWords.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true, "tags": [] }, "outputs": [], "source": [ "BHSallHebrewWords=BHSallWords[(BHSallWords['language1']=='Hebrew') & (BHSallWords['S1']=='Genesis')]\n", "BHSallHebrewWords.head() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Selecting only Vocab for OTST551 Glanz course (Genesis 19-20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "Gen19v='''\n", "verse book=Genesis chapter=19 verse=21|22|23|25|27|29|30\n", " word lex* bol_dict_HebArm* bol_dict_EN* number* freq_occ* rank_occ* bol_fa_order* bol_lexeme_occurrences* bol_dict_abc* language* bol_monad_num* qere_utf8* g_word_utf8* g_lex_utf8* bol_g_word_utf8* bol_qere_presence*\n", "\n", "'''\n", "Gen19v = BHSa4c.search(Gen19v)\n", "BHSa4c.table(Gen19v, start=1, end=5, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Gen19v, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises', toFile='Gen19v.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Selecting only Vocab of Jeremiah" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallWords=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_vocab_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "BHSallWords.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "BHSallHebrewWords=BHSallWords[(BHSallWords['language1']=='Hebrew') & (BHSallWords['S1']=='Psalms')]\n", "BHSallHebrewWords.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST552 Midterm (Hebrew II)\n", "#### Part 1" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Midterm_Vocab_Text01='''\n", "verse book=Genesis chapter=20 verse=6|7|8|9\n", " w1:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences>100 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", " w2:word bol_lexeme_occurrences<6000\n", "\n", "w1 = w2\n", "\n", "\n", "'''\n", "OTST552Midterm_Vocab_Text01 = BHSa4c.search(OTST552Midterm_Vocab_Text01)\n", "BHSa4c.table(OTST552Midterm_Vocab_Text01, start=1, end=1, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Midterm_Vocab_Text01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_vocabulary_Heb-II_Midterm_Vocab_Text01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Part 2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Midterm_Vocab_Text02='''\n", "v1:verse book=Reges_I chapter=3 verse=3\n", " w1:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences>100 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", " w2:word bol_lexeme_occurrences<6000\n", "\n", "w1 = w2\n", "\n", "\n", "'''\n", "OTST552Midterm_Vocab_Text02 = BHSa4c.search(OTST552Midterm_Vocab_Text02)\n", "BHSa4c.table(OTST552Midterm_Vocab_Text02, start=1, end=1, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Midterm_Vocab_Text02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_vocabulary_Heb-II_Midterm_Vocab_Text02.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [], "toc-hr-collapsed": true }, "source": [ "## Complete Phonology" ] }, { "attachments": { "image.png": { "image/png": "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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "### Prefixing\n", "#### Prefixing Waw\n", "![image.png](attachment:image.png)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingAll='''\n", "c:clause\n", " w1:word lex=W g_word~^W:-|^W@-|^WI-|^WA-|^WE- bol_dict_HebArm* number* freq_occ* rank_occ* freq_lex bol_dict_abc* language=Hebrew bol_monad_num\n", " w2:word g_word~^[>BGDHWZXVJKLMNSBGDHWZXVJKLMNSHX<]:E|^[>HX<]:A|^[>HX<]:@ sp=subs|nmpr bol_monad_num\n", "\n", "w1 <: w2\n", "\n", "\n", "'''\n", "Hebrew_PrefixingAll = BHSa4c.search(Hebrew_PrefixingAll)\n", "BHSa4c.table(Hebrew_PrefixingAll, start=1, end=10, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingW1='''\n", "c:clause\n", " w1:word lex=W g_word~^W:- bol_dict_HebArm* number* freq_occ* rank_occ* freq_lex bol_dict_abc* language=Hebrew bol_monad_num\n", " w2:word g_word~^[>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHX<]:@[>BGDHWZXVJKLMNSHX<]:A[>BGDHWZXVJKLMNSHX<]:E[>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHX<]:@[>BGDHWZXVJKLMNSHX<]:A[>BGDHWZXVJKLMNSHX<]:E[>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHX<] sp=subs|nmpr bol_monad_num\n", "\n", "w1 <: w2\n", "\n", "\n", "'''\n", "Hebrew_PrefixingMN2 = BHSa4c.search(Hebrew_PrefixingMN2)\n", "BHSa4c.table(Hebrew_PrefixingMN2, start=1, end=50, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Hebrew_PrefixingMN2, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_morphology_prefixingMN2_exercises.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingMN2=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_morphology_prefixingMN2_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "Hebrew_PrefixingMN2.head()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "Hebrew_PrefixingMN2selection=Hebrew_PrefixingMN2 \\\n", " .groupby(['TEXT2']) \\\n", " .sample(n=5, replace=True)\\\n", " .sort_values(['TEXT2','bol_monad_num2'], \n", " ascending=True)\n", "Hebrew_PrefixingMN2selection.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingMN2selection.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_Hebrew_morphology_PrefixingMN2selection.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Prefixing article" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingH1='''\n", "c:clause\n", " w1:word lex=H g_word~^HA- bol_dict_HebArm* number* freq_occ* rank_occ* freq_lex bol_dict_abc* language=Hebrew bol_monad_num\n", " w2:word g_word~^[BGDWZVJKLMNSPYQFCT] sp=subs|nmpr bol_monad_num\n", "\n", "w1 <: w2\n", "\n", "\n", "'''\n", "Hebrew_PrefixingH1 = BHSa4c.search(Hebrew_PrefixingH1)\n", "BHSa4c.table(Hebrew_PrefixingH1, start=1, end=50, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Hebrew_PrefixingH1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_morphology_prefixingH1_exercises.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingH1=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_morphology_prefixingH1_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "Hebrew_PrefixingH1.head()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "Hebrew_PrefixingH1selection=Hebrew_PrefixingH1 \\\n", " .groupby(['TEXT2']) \\\n", " .sample(n=5, replace=True)\\\n", " .sort_values(['TEXT2','bol_monad_num2'], \n", " ascending=True)\n", "Hebrew_PrefixingH1selection.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingH1selection.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_Hebrew_morphology_PrefixingH1selection.xlsx', encoding='utf-16')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Hebrew_PrefixingH2='''\n", "c:clause\n", " w1:word lex=H g_word~^H@- bol_dict_HebArm* number* freq_occ* rank_occ* freq_lex bol_dict_abc* language=Hebrew bol_monad_num\n", " w2:word g_word~^[>BGDHWZXVJKLMNS 1300)\n", " &((BibleOL_PRS_morphology['sp'] == 'prep') \n", " |(BibleOL_PRS_morphology['sp'] == 'subs')\n", " )\n", " & ((BibleOL_PRS_morphology['nu'] == 'sg') \n", " |(BibleOL_PRS_morphology['nu'] == 'pl') \n", " |(BibleOL_PRS_morphology['nu'].isna()) \n", " )\n", " )\n", " ]\n", "BibleOL_PRS_morphology1.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-06T10:08:44.542239Z", "start_time": "2022-06-06T10:08:44.462110Z" } }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BibleOL_PRS_morphology1=BibleOL_PRS_morphology1 \\\n", " .groupby(['sp',\n", " 'prs_ps',\n", " 'prs_nu',\n", " 'prs_gn',\n", " ]) \\\n", " .sample(n=5, replace=True)\\\n", " .sort_values(['prs_ps',\n", " 'prs_nu',\n", " 'prs_gn',\n", " 'bol_monad_num'],\n", " ascending=[True,False,True,True])\n", "BibleOL_PRS_morphology1.head(100)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-06T10:08:46.059971Z", "start_time": "2022-06-06T10:08:45.966454Z" } }, "outputs": [], "source": [ "BibleOL_PRS_morphology1.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_morphology_Suffixation_selection.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Retrieving Nominal Forms" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Retrieving Verbal Forms" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2023-01-16T22:42:59.491507Z", "start_time": "2023-01-16T22:42:52.195326Z" } }, "outputs": [], "source": [ "Search1='''\n", "word bol_monad_num* bol_qere_presence=0 bol_vt=perf|impf|wayq|juss|coho|impv|infa|infc|ptca|ptcp lex* number* freq_occ* freq_lex* st* rank_occ* bol_dict_abc* bol_dict_HebArm bol_bhsa_word_order* bol_dict_vc* ps* nu* gn* vt* vs prs_nu* prs_ps* prs_gn* sp=verb pdp* bol_dict_EN g_word_noaccent language=Hebrew \n", "\n", "'''\n", "Search1 = BHSa4c.search(Search1)\n", "BHSa4c.table(Search1, start=1, end=2, multiFeatures=True, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T19:51:07.031470Z", "start_time": "2022-06-02T19:50:56.289207Z" } }, "outputs": [], "source": [ "BHSa4c.export(Search1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_verbal-morphology_Heb-I-II-III_exercises.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallVerbalMorphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_verbal-morphology_Heb-I-II-III_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "vc=BHSallVerbalMorphology.bol_dict_vc1.unique().tolist()\n", "print(vc)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Excluding 4 root verbs" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphology=BHSallVerbalMorphology[(BHSallVerbalMorphology['bol_dict_vc1']!='4 root verb') & (BHSallVerbalMorphology['language1']=='Hebrew')]\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphologyOTST551_552=BHSallVerbalMorphology[(BHSallVerbalMorphology['bol_dict_vc1']!='4 root verb') & (BHSallVerbalMorphology['language1']=='Hebrew')]\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Retrieving 2 samples of each verbal form" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHSallVerbalMorphology=BHSallVerbalMorphology \\\n", " .groupby(['bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1']) \\\n", " .sample(n=2, replace=True)\\\n", " .sort_values(['bol_monad_num1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1'], \n", " ascending=True)\n", "BHSallVerbalMorphology.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphology.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/OTST551_Heb-I-II-III_verbal-morphology_selection_of_2.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exam Selection" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "OTST625ExamWords1='''\n", "verse book=Judices chapter=19 verse=22|23|24|25|26|27|28|29\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST625ExamWords1 = BHSa4c.search(OTST625ExamWords1)\n", "BHSa4c.table(OTST625ExamWords1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphology.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/OTST551_Heb-I-II-III_verbal-morphology_selection_of_2.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Word level exam parts for OTST551" ] }, { "cell_type": "markdown", "metadata": { "tags": [], "toc-hr-collapsed": true }, "source": [ "### Vocab for Hebrew I exams (OTST551 Glanz course on Genesis 19 and Genesis 20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST551ExamWords='''\n", "chapter book=Genesis chapter=19|20\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST551ExamWords = BHSa4c.search(OTST551ExamWords)\n", "BHSa4c.show(OTST551ExamWords, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST551ExamWords, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-I_OTST551-Glanz-course_ExamWords.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### OTST552 Midterm (Hebrew II) - Morphology\n", "#### Part 01" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Text1_VerbalMorphology='''\n", "verse book=Genesis chapter=20 verse=6|7|8|9\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552_Text1_VerbalMorphology = BHSa4c.search(OTST552_Text1_VerbalMorphology)\n", "BHSa4c.table(OTST552_Text1_VerbalMorphology, start=1, end=26, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Text1_VerbalMorphology, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_morphology-verb_Heb-II_Midterm_VerbalMorphology_Text01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Part 02" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Text2_VerbalMorphology='''\n", "verse book=Reges_I chapter=3 verse=3\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552_Text2_VerbalMorphology = BHSa4c.search(OTST552_Text2_VerbalMorphology)\n", "BHSa4c.table(OTST552_Text2_VerbalMorphology, start=1, end=4, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Text2_VerbalMorphology, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_morphology-verb_Heb-II_Midterm_VerbalMorphology_Text02.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Text3_VerbalMorphology='''\n", "verse book=Genesis chapter=19 verse=13|14\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552_Text3_VerbalMorphology = BHSa4c.search(OTST552_Text3_VerbalMorphology)\n", "BHSa4c.table(OTST552_Text3_VerbalMorphology, start=1, end=26, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Text3_VerbalMorphology, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_morphology-verb_Heb-II_Midterm_VerbalMorphology_Text03.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Phrases for Hebrew I" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PhraseFunction1='''\n", "clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", " /-/\n", " /without/\n", " word lex=LQX[\n", " /-/\n", " phrase function* typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_num_phrase* bol_sequence_num_phrase_atom* bol_lexeme_occurrences* bol_sequence_num_clause* bol_sequence_num_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "PhraseFunction1 = BHSa4c.search(PhraseFunction1)\n", "BHSa4c.show(PhraseFunction1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-I_exercises.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Complete Phrase analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### subphrase" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:11.774698Z", "start_time": "2022-06-30T18:17:10.976727Z" } }, "outputs": [], "source": [ "SubPhrase='''\n", "p:phrase\n", "/without/\n", " word ls=ordn|card\n", "/-/\n", "/without/\n", " word bol_lexeme_occurrences<69\n", "/-/\n", "/without/\n", " word lex=JHWH/\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", " sub1:subphrase rela*\n", " word bol_sequence_number_subphrase* bol_lexeme_occurrences* language=Hebrew ls* lex*\n", " sub2:subphrase rela=atr|dem|rec\n", " word bol_sequence_number_subphrase* bol_lexeme_occurrences* language=Hebrew ls* lex*\n", "\n", "p =: sub1\n", "p := sub2\n", "sub1 <: sub2\n", "\n", "\n", "'''\n", "SubPhrase = BHSa4c.search(SubPhrase)\n", "BHSa4c.show(SubPhrase, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:20.524882Z", "start_time": "2022-06-30T18:17:11.775974Z" } }, "outputs": [], "source": [ "BHSa4c.export(SubPhrase, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_subphrase_exercise.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "SubPhrase=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_subphrase_exercise.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "SubPhrase.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhrase.rela4.unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhrasePart1=SubPhrase[((SubPhrase['rela4'] == 'rec')\n", " | (SubPhrase['rela4'] == 'atr'))]\n", "SubPhrasePart1.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "SubPhrasePart1=SubPhrasePart1 \\\n", " .groupby(['rela4']) \\\n", " .sample(n=100, replace=True)\\\n", " .sort_values(['rela4'], \n", " ascending=True)\n", "SubPhrasePart1.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "SubPhrasePart1.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_subphrase-relations_part1_Heb-I_exercises.xlsx', encoding='utf-16')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhrasePart2=SubPhrase[((SubPhrase['rela4'] == 'dem'))]\n", "SubPhrasePart2.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhrasePart2 = SubPhrasePart2[((SubPhrasePart2['lex5'] != \"H\"))]\n", "SubPhrasePart2.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhrasePart2.lex5.unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "SubPhrasePart2=SubPhrasePart2 \\\n", " .groupby(['lex5']) \\\n", " .sample(n=17, replace=True)\\\n", " .sort_values(['lex5'], \n", " ascending=True)\n", "SubPhrasePart2.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "SubPhrasePart2.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_subphrase-relations_part2_Heb-I_exercises.xlsx', encoding='utf-16')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhraseP1=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_subphrase-relations_part1_Heb-I_exercises.xlsx')\n", "SubPhraseP1.head()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhraseP2=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_subphrase-relations_part2_Heb-I_exercises.xlsx')\n", "SubPhraseP2.head()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhraseAll = pd.concat([SubPhraseP1,SubPhraseP2], axis=0)\n", "SubPhraseAll.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhraseAll.rela4.unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SubPhraseAll.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_subphrase-relations_all_Heb-I_exercises.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### phrase" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:21.748638Z", "start_time": "2022-06-30T18:17:20.526526Z" } }, "outputs": [], "source": [ "PhraseFunction0='''\n", "c:clause\n", "/without/\n", " word bol_lexeme_occurrences<1\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^i.*|geminate\n", "/-/\n", "/without/\n", " word lex=LQX[\n", "/-/\n", " p1:phrase function=Subj|Objc|Pred|PreO|Nega\n", " word bol_sequence_num_phrase* bol_lexeme_occurrences* bol_sequence_num_clause* bol_monad_num*\n", " p2:phrase function=Subj|Objc|Pred|PreO|Nega\n", " word bol_sequence_num_phrase* bol_lexeme_occurrences* bol_sequence_num_clause* bol_monad_num*\n", " p3:phrase function=Subj|Objc|Pred|PreO|Nega\n", " word bol_sequence_num_phrase* bol_lexeme_occurrences* bol_sequence_num_clause* bol_monad_num*\n", "\n", "p1 < p2\n", "p2 < p3\n", "\n", "\n", "'''\n", "PhraseFunction0 = BHSa4c.search(PhraseFunction0)\n", "BHSa4c.show(PhraseFunction0, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:31.302391Z", "start_time": "2022-06-30T18:17:21.749319Z" } }, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction0, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase_exercise.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "PhraseFunction0=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_phrase_exercise.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "PhraseFunction0.head(20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "PhraseFunction0.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_phrase_Heb1_exercise.xlsx', encoding='utf-16')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "PhraseFunction0=PhraseFunction0 \\\n", " .groupby(['function2']) \\\n", " .sample(n=10, replace=True)\\\n", " .sort_values(['R'], \n", " ascending=True)\n", "PhraseFunction0.head(100)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "PhraseFunction0.to_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_phrase_Heb1_exercise.csv', sep ='\\t')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases for Hebrew I (OTST551 Glanz course on Genesis 19 and Genesis 20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST551Phrases1='''\n", "chapter book=Genesis chapter=19|20\n", " clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " phrase function=Pred|PreO|PreS|PreC|Objc|Subj|Cmpl typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST551Phrases1 = BHSa4c.search(OTST551Phrases1)\n", "BHSa4c.show(OTST551Phrases1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST551Phrases1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-I_OTST551-Glanz-course_FinalExamPhrases1.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases for Hebrew I" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PhraseFunction1='''\n", "clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", " /-/\n", " /without/\n", " word lex=LQX[\n", " /-/\n", " phrase function* typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_num_phrase* bol_sequence_num_phrase_atom* bol_lexeme_occurrences* bol_sequence_num_clause* bol_sequence_num_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "PhraseFunction1 = BHSa4c.search(PhraseFunction1)\n", "BHSa4c.show(PhraseFunction1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-I_exercises.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases for Hebrew I with Vocab of >200 occ only" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PhraseFunction3='''\n", "c1:clause typ* kind=NC|VC|WP rela* domain*\n", "/without/\n", " word bol_lexeme_occurrences<200\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "c2:clause typ* kind=NC|VC|WP rela* domain*\n", "/without/\n", " word bol_lexeme_occurrences<200\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "c3:clause typ* kind=NC|VC|WP rela* domain*\n", "/without/\n", " word bol_lexeme_occurrences<200\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", " \n", "c1 <: c2\n", "c2 <: c3\n", "\n", "'''\n", "PhraseFunction3 = BHSa4c.search(PhraseFunction3)\n", "BHSa4c.show(PhraseFunction3, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction3, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_phrase-function_Heb-I-Voc200_exercises.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases for Hebrew II with Vocab of >100 occ only\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PhraseFunction4='''\n", "c1:clause typ* kind=NC|VC|WP rela* domain*\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "c2:clause typ* kind=NC|VC|WP rela* domain*\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "c3:clause typ* kind=NC|VC|WP rela* domain*\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", " \n", "c1 <: c2\n", "c2 <: c3\n", "\n", "'''\n", "PhraseFunction4 = BHSa4c.search(PhraseFunction4)\n", "BHSa4c.show(PhraseFunction4, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction4, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_phrase-function_Heb-II-Voc100_exercises.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases for Hebrew II-III with NO vocab restriction\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PhraseFunction5='''\n", "clause typ* kind=NC|VC|WP rela* domain*\n", " phrase function=Pred|PreO|PreS|PreC|Subj|Objc|Cmpl|Voct|Nega typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "PhraseFunction5 = BHSa4c.search(PhraseFunction5)\n", "BHSa4c.show(PhraseFunction5, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction5, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_phrase-function_Heb-II-III_NoVocabLimit_exercises.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST552 Midterm (Hebrew II)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Part 01" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Midterm_PhraseFunction_Part01='''\n", "verse book=Genesis chapter=20 verse=6|7|8|9\n", " clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl typ* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "OTST552Midterm_PhraseFunction_Part01 = BHSa4c.search(OTST552Midterm_PhraseFunction_Part01)\n", "BHSa4c.show(OTST552Midterm_PhraseFunction_Part01, start=1, end=1, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Midterm_PhraseFunction_Part01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-II_Midterm_PhraseFunction_Part01.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Part 02" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Midterm_PhraseFunction_Part02='''\n", "v1:verse book=Reges_I\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", " clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl typ* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "v2:verse\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", "\n", "v1 <: v2\n", "\n", "\n", "'''\n", "OTST552Midterm_PhraseFunction_Part02 = BHSa4c.search(OTST552Midterm_PhraseFunction_Part02)\n", "BHSa4c.table(OTST552Midterm_PhraseFunction_Part02, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Midterm_PhraseFunction_Part02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-II_Midterm_PhraseFunction_Part02.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Midterm_PhraseFunction_Part02='''\n", "v1:verse book=Reges_I chapter=3 verse=3\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", " clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl typ* det*\n", " phrase_atom function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "OTST552Midterm_PhraseFunction_Part02 = BHSa4c.search(OTST552Midterm_PhraseFunction_Part02)\n", "BHSa4c.table(OTST552Midterm_PhraseFunction_Part02, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Midterm_PhraseFunction_Part02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-II_Midterm_PhraseFunction_Part02.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST552 Qualifier\n", "#### selected chapters" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PhraseFunctionQualifier1='''\n", "clause typ* kind* rela* domain*\n", " clause_atom rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word bol_lexeme_occurrences<69\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " word lex=LQX[\n", " /-/\n", " p1:phrase function=Voct|Subj|Objc|Cmpl|PreS|PreO|PreC|Pred| typ* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "PhraseFunctionQualifier1 = BHSa4c.search(PhraseFunctionQualifier1)\n", "BHSa4c.show(PhraseFunctionQualifier1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(PhraseFunctionQualifier1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_phrase-function_QUALIFIER_exercises.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### phrase_atom" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:32.608424Z", "start_time": "2022-06-30T18:17:31.304675Z" } }, "outputs": [], "source": [ "PhraseAtom='''\n", "phrase_atom number rela\n", " word bol_monad_num*\n", "\n", "'''\n", "PhraseAtom = BHSa4c.search(PhraseAtom)\n", "BHSa4c.show(PhraseAtom, start=1, end=5, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:41.777287Z", "start_time": "2022-06-30T18:17:32.609145Z" } }, "outputs": [], "source": [ "BHSa4c.export(PhraseAtom, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew', toFile='BHSa4c_BOL_phrase_atom.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Complete Clause Relation analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### clause" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:42.764522Z", "start_time": "2022-06-30T18:17:41.778374Z" } }, "outputs": [], "source": [ "ClauseFunction='''\n", "clause typ number\n", "\n", "'''\n", "ClauseFunction = BHSa4c.search(ClauseFunction)\n", "BHSa4c.show(ClauseFunction, start=1, end=5, extraFeatures={}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:52.175305Z", "start_time": "2022-06-30T18:17:42.765816Z" } }, "outputs": [], "source": [ "BHSa4c.export(PhraseFunction, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew', toFile='BHSa4c_BOL_clause.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST552 Midterm (Hebrew II)\n", "#### Part 01" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Midterm_ClauseRela_Part01='''\n", "verse book=Genesis chapter=20 verse=6|7|8|9\n", " clause typ#Voct kind* rela#RgRc|Resu|PreC|Coor|PrAd|Spec|ReVo|Adju domain*\n", " clause_atom typ*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "OTST552Midterm_ClauseRela_Part01 = BHSa4c.search(OTST552Midterm_ClauseRela_Part01)\n", "BHSa4c.show(OTST552Midterm_ClauseRela_Part01, start=1, end=1, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Midterm_ClauseRela_Part01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_clause-syntax_Heb-II_Midterm_ClauseRela_Part01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### clause_atom rela for Hebrew I (OTST551 Glanz course on Genesis 19 and Genesis 20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:53.187328Z", "start_time": "2022-06-30T18:17:52.176192Z" } }, "outputs": [], "source": [ "OTST551ClauseAtomRela1='''\n", "chapter book=Genesis chapter=19|20\n", " clause rela*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "OTST551ClauseAtomRela1 = BHSa4c.search(OTST551ClauseAtomRela1)\n", "BHSa4c.show(OTST551ClauseAtomRela1, start=1, end=5, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST551ClauseAtomRela1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-I_OTST551-Glanz-course_FinalExamClauseAtomRela1.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### clause rela for Hebrew I with vocab >200" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:53.187328Z", "start_time": "2022-06-30T18:17:52.176192Z" } }, "outputs": [], "source": [ "OTST551ClauseAtomRela1='''\n", "c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", "/without/\n", " word bol_lexeme_occurrences<200\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "c2:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", "/without/\n", " word bol_lexeme_occurrences<200\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "c1 <: c2\n", "\n", "'''\n", "OTST551ClauseAtomRela1 = BHSa4c.search(OTST551ClauseAtomRela1)\n", "BHSa4c.show(OTST551ClauseAtomRela1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST551ClauseAtomRela1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_clause-rela_Heb-I-Vocab200_exercise.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### clause rela for Hebrew II with vocab >100" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:53.187328Z", "start_time": "2022-06-30T18:17:52.176192Z" } }, "outputs": [], "source": [ "OTST552ClauseAtomRela1='''\n", "c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "c2:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "c1 <: c2\n", "\n", "'''\n", "OTST552ClauseAtomRela1 = BHSa4c.search(OTST552ClauseAtomRela1)\n", "BHSa4c.show(OTST552ClauseAtomRela1, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552ClauseAtomRela1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_clause-rela_Heb-II-Vocab100_exercise.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### clause rela for Hebrew II-III with NO vocab restriction" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:53.187328Z", "start_time": "2022-06-30T18:17:52.176192Z" } }, "outputs": [], "source": [ "OTST552ClauseAtomRela2='''\n", "c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", "/without/\n", " word bol_qere_presence=1\n", "/-/\n", "/without/\n", " word language=Aramaic\n", "/-/\n", "/without/\n", " word bol_dict_vc~^four.*verb|^gemi.*|^i.*\n", "/-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "OTST552ClauseAtomRela2 = BHSa4c.search(OTST552ClauseAtomRela2)\n", "BHSa4c.show(OTST552ClauseAtomRela2, start=1, end=2, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552ClauseAtomRela2, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_syntax_clause-rela_Heb-II-III_NoVocabLimit_exercise.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### clause_atom rela" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:53.187328Z", "start_time": "2022-06-30T18:17:52.176192Z" } }, "outputs": [], "source": [ "ClauseAtom='''\n", "clause_atom typ number\n", " word bol_monad_num*\n", "\n", "'''\n", "ClauseAtom = BHSa4c.search(ClauseAtom)\n", "BHSa4c.show(ClauseAtom, start=1, end=5, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:18:04.000782Z", "start_time": "2022-06-30T18:17:53.188027Z" } }, "outputs": [], "source": [ "BHSa4c.export(ClauseAtom, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew', toFile='BHSa4c_BOL_clause_atom.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Clauses from the Book of Jonah" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:17:53.187328Z", "start_time": "2022-06-30T18:17:52.176192Z" } }, "outputs": [], "source": [ "ClauseRelationsJonah1='''\n", "book book=Jona\n", " clause typ rela=NA|Attr|Objc number\n", " word bol_monad_num*\n", "\n", "'''\n", "ClauseRelationsJonah1 = BHSa4c.search(ClauseRelationsJonah1)\n", "BHSa4c.table(ClauseRelationsJonah1, start=1, end=5, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(ClauseRelationsJonah1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises', toFile='BHSa4c_BOL_clause-relations_Jonah.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Sentence analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### sentence" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:18:05.016208Z", "start_time": "2022-06-30T18:18:04.003712Z" } }, "outputs": [], "source": [ "Sentence='''\n", "sentence number\n", " word bol_monad_num*\n", "\n", "'''\n", "Sentence = BHSa4c.search(Sentence)\n", "BHSa4c.show(Sentence, start=1, end=5, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:18:14.266733Z", "start_time": "2022-06-30T18:18:05.017038Z" } }, "outputs": [], "source": [ "BHSa4c.export(Sentence, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew', toFile='BHSa4c_BOL_sentence.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### sentence_atom" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:34:45.970984Z", "start_time": "2022-06-30T18:34:45.052201Z" } }, "outputs": [], "source": [ "SentenceAtom='''\n", "sentence_atom number\n", " word bol_monad_num*\n", "\n", "'''\n", "SentenceAtom = BHSa4c.search(SentenceAtom)\n", "BHSa4c.show(SentenceAtom, start=1, end=5, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T18:35:07.124766Z", "start_time": "2022-06-30T18:34:55.521374Z" } }, "outputs": [], "source": [ "BHSa4c.export(SentenceAtom, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew', toFile='BHSa4c_BOL_sentence_atom.tsv')" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2022-06-30T16:42:39.970670Z", "start_time": "2022-06-30T16:42:39.941026Z" } }, "source": [ "### Merging the BOL wordsequence data with the TF subphrase,phrase,clause,and sentence information" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T17:44:02.277122Z", "start_time": "2022-06-30T17:42:42.699074Z" } }, "outputs": [], "source": [ "BOL_ETCBC4c_data=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercise-selection_20220701.xlsx', sheet_name='BOL_ETCBC4_database_20220630_nu')\n", "pd.set_option('display.max_columns', 50)\n", "BOL_ETCBC4c_data.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T17:44:02.314966Z", "start_time": "2022-06-30T17:44:02.279051Z" } }, "outputs": [], "source": [ "BOL_ETCBC4c_data.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Prepping" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:53.447330Z", "start_time": "2022-06-30T19:01:53.026616Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_subphrase=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_subphrase.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_subphrase.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:53.702643Z", "start_time": "2022-06-30T19:01:53.661455Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_subphrase.rename(columns={'bol_monad_num2':'monad_num', 'rela1':'subphrase_rela', 'TEXT1':'subphrase', 'TEXT2':'word'}, inplace=True)\n", "\n", "TF_ETCBC4c_subphrase = TF_ETCBC4c_subphrase.drop(columns=['R','S1','S2','S3','TYPE1', 'NODE1', 'NODE2', 'TYPE2'])\n", "\n", "\n", "TF_ETCBC4c_subphrase.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:54.112546Z", "start_time": "2022-06-30T19:01:54.081791Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_subphrase.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:54.886295Z", "start_time": "2022-06-30T19:01:54.414246Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_phrase=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_phrase.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_phrase.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:54.914206Z", "start_time": "2022-06-30T19:01:54.887459Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_phrase.rename(columns={'bol_monad_num2':'monad_num', 'function1':'function', 'TEXT1':'phrase', 'number1':'phrase_number', 'typ1':'phrase_type'}, inplace=True)\n", "\n", "TF_ETCBC4c_phrase = TF_ETCBC4c_phrase.drop(columns=['R','S1','S2','S3','TYPE1', 'NODE1', 'NODE2', 'TYPE2','TEXT2'])\n", "\n", "\n", "TF_ETCBC4c_phrase.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:55.124995Z", "start_time": "2022-06-30T19:01:55.103078Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_phrase.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:55.923031Z", "start_time": "2022-06-30T19:01:55.481425Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_phrase_atom=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_phrase_atom.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_phrase_atom.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:55.947762Z", "start_time": "2022-06-30T19:01:55.924553Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_phrase_atom.rename(columns={'bol_monad_num2':'monad_num', 'TEXT1':'phrase_atom', 'rela1':'phrase_atom_rela','number1':'phrase_atom_number', 'typ1':'phrase_type'}, inplace=True)\n", "\n", "TF_ETCBC4c_phrase_atom = TF_ETCBC4c_phrase_atom.drop(columns=['R','S1','S2','S3','TYPE1', 'NODE1', 'NODE2', 'TYPE2', 'TEXT2'])\n", "\n", "\n", "TF_ETCBC4c_phrase_atom.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:56.245938Z", "start_time": "2022-06-30T19:01:56.214422Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_phrase_atom.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:57.387866Z", "start_time": "2022-06-30T19:01:56.970480Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_clause=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_clause.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_clause.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:57.414896Z", "start_time": "2022-06-30T19:01:57.398991Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_clause.rename(columns={'bol_monad_num2':'monad_num'}, inplace=True)\n", "\n", "TF_ETCBC4c_clause = TF_ETCBC4c_clause.drop(columns=['R','S1','S2','S3','TEXT1','TYPE1', 'typ1','NODE1', 'NODE2', 'TYPE2','TEXT2','number1'])\n", "\n", "\n", "TF_ETCBC4c_clause.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:57.950874Z", "start_time": "2022-06-30T19:01:57.921863Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_clause.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:01:58.965368Z", "start_time": "2022-06-30T19:01:58.417567Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_clause_atom=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_clause_atom.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_clause_atom.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:00.955320Z", "start_time": "2022-06-30T19:02:00.908504Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_clause_atom.rename(columns={'bol_monad_num2':'monad_num', 'TEXT1':'clause_atom', 'rela1':'clause_atom_rela','typ1':'clause_atom_typ','number1':'clause_atom_number', 'typ1':'clause_atom_type'}, inplace=True)\n", "\n", "TF_ETCBC4c_clause_atom = TF_ETCBC4c_clause_atom.drop(columns=['R','S1','S2','S3','TYPE1', 'NODE1', 'NODE2', 'TYPE2', 'TEXT2'])\n", "\n", "\n", "TF_ETCBC4c_clause_atom.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:03.490951Z", "start_time": "2022-06-30T19:02:03.459552Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_clause_atom.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:05.568845Z", "start_time": "2022-06-30T19:02:05.172499Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_sentence=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_sentence.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_sentence.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:05.777850Z", "start_time": "2022-06-30T19:02:05.752269Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_sentence.rename(columns={'bol_monad_num2':'monad_num'}, inplace=True)\n", "\n", "TF_ETCBC4c_sentence = TF_ETCBC4c_sentence.drop(columns=['R','S1','S2','S3','TYPE1','TEXT1', 'NODE1', 'NODE2', 'TYPE2','TEXT2','number1'])\n", "\n", "\n", "TF_ETCBC4c_sentence.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:06.401617Z", "start_time": "2022-06-30T19:02:06.374748Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_sentence.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:07.704053Z", "start_time": "2022-06-30T19:02:07.083280Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_sentence_atom=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_sentence_atom.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "TF_ETCBC4c_sentence_atom.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:07.726027Z", "start_time": "2022-06-30T19:02:07.705066Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_sentence_atom.rename(columns={'bol_monad_num2':'monad_num', 'TEXT1':'sentence_atom', 'number1':'sentence_atom_number'}, inplace=True)\n", "\n", "TF_ETCBC4c_sentence_atom = TF_ETCBC4c_sentence_atom.drop(columns=['R','S1','S2','S3','TYPE1', 'NODE1', 'NODE2', 'TYPE2', 'TEXT2'])\n", "\n", "\n", "TF_ETCBC4c_sentence_atom.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:02:12.547877Z", "start_time": "2022-06-30T19:02:12.513361Z" } }, "outputs": [], "source": [ "TF_ETCBC4c_sentence_atom.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Merging" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:10.009274Z", "start_time": "2022-06-30T19:03:09.667019Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge1=pd.merge(BOL_ETCBC4c_data, TF_ETCBC4c_subphrase,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge1.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:11.269445Z", "start_time": "2022-06-30T19:03:10.893573Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge2=pd.merge(BOL_TF_4c_merge1, TF_ETCBC4c_phrase_atom,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge2.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:11.839344Z", "start_time": "2022-06-30T19:03:11.438774Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge3=pd.merge(BOL_TF_4c_merge2, TF_ETCBC4c_phrase,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge3.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:12.705538Z", "start_time": "2022-06-30T19:03:12.251528Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge4=pd.merge(BOL_TF_4c_merge3, TF_ETCBC4c_clause_atom,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge4.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:13.415914Z", "start_time": "2022-06-30T19:03:12.986930Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge5=pd.merge(BOL_TF_4c_merge4, TF_ETCBC4c_clause,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge5.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:14.056362Z", "start_time": "2022-06-30T19:03:13.798260Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge6=pd.merge(BOL_TF_4c_merge5, TF_ETCBC4c_sentence_atom,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge6.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:15.314955Z", "start_time": "2022-06-30T19:03:14.956883Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge7=pd.merge(BOL_TF_4c_merge6, TF_ETCBC4c_sentence,\n", " on=['monad_num'],\n", " how='left')\n", "BOL_TF_4c_merge7.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:03:17.312487Z", "start_time": "2022-06-30T19:03:17.151539Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge7.rename(columns={'verse':'reference','bol_monad_num2':'monad_num','S1':'book','S2':'chapter','S3':'verse','phrase_atom_y':'phrase_atom','phrase_type_y':'phrase_type'}, inplace=True)\n", "\n", "BOL_TF_4c_merge7 = BOL_TF_4c_merge7.drop(columns=['R','TYPE1','TEXT1', 'word'])\n", "\n", "\n", "BOL_TF_4c_merge7.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:04:31.993312Z", "start_time": "2022-06-30T19:04:31.942189Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge = BOL_TF_4c_merge7" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:04:32.811145Z", "start_time": "2022-06-30T19:04:32.781479Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Export" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-30T19:10:54.547691Z", "start_time": "2022-06-30T19:04:43.022813Z" } }, "outputs": [], "source": [ "BOL_TF_4c_merge.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BOL_exercises/BOL_ETCBC_4c_complete-database_20220701.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Looking for Verbal Classes\n", "Here are the classes:\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "| position i | position ii | position iii | position iv |\n", "|:-------|:------|:------|:-----|\n", "|regular||||\n", "|i-guttural|ii-guttural|iii-guttural||\n", "|i-aleph||iii-aleph||\n", "|i-waw|ii-waw|||\n", "|i-yod|ii-yod|||\n", "|i-nun||||\n", "||geminate|||\n", "|||iii-hey||\n", "||||iv-root|\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T14:18:23.070717Z", "start_time": "2022-03-28T14:18:21.973278Z" } }, "outputs": [], "source": [ "HebrewWordRank_1to20='''\n", "verse book=Genesis chapter=1|2|3|4|5|6|7|8|9|10\n", " word lex=W|H|L|B|>T|MN|JHWH/|L|>CR|KL/|>MR[|L>|BN/|KJ|HJH[|K|LHJM/|BW>[ number* freq_occ* rank_occ* bol_dict_abc*\n", "\n", "'''\n", "HebrewWordRank_1to20 = BHSa4c.search(HebrewWordRank_1to20)\n", "BHSa4c.table(HebrewWordRank_1to20, start=1, end=23, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-05-07T14:32:11.884969Z", "start_time": "2022-05-07T14:32:11.849714Z" } }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(HebrewWordRank_1to20, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-Personal/4001_publication-presentation/0_pub-book_2023_HebrewVocabBooklet', toFile='HebrewWordRank_1to20.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T14:18:28.096647Z", "start_time": "2022-03-28T14:18:28.042947Z" } }, "outputs": [], "source": [ "HebrewWordRank_1to20=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-Personal/4001_publication-presentation/0_pub-book_2023_HebrewVocabBooklet/HebrewWordRank_1to20.tsv',delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "HebrewWordRank_1to20.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "No we only want to show the first two appearances of each word bu using the `nth` function.\n", "\n", "\n", "See the discussion here: https://www.statology.org/pandas-first-row-of-each-group/" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T14:19:58.762188Z", "start_time": "2022-03-28T14:19:58.704781Z" } }, "outputs": [], "source": [ "HebrewWordRank_1to20.groupby('lex2').nth((0,1)).sort_values(['bol_dict_abc2'], ascending=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T14:43:05.760487Z", "start_time": "2022-03-28T14:43:05.680328Z" } }, "outputs": [], "source": [ "list=HebrewWordRank_1to20.groupby('lex2').nth((0,1)).sort_values(['bol_dict_abc2'], ascending=True)\n", "list.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T14:54:10.018179Z", "start_time": "2022-03-28T14:54:09.938508Z" } }, "outputs": [], "source": [ "list.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-Personal/4001_publication-presentation/0_pub-book_2023_HebrewVocabBooklet/HebrewWordRank_BOL_1to20.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Production" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T15:36:52.329497Z", "start_time": "2022-03-28T15:36:50.677708Z" } }, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab='''\n", "word lex* bol_dict_HebArm* number* freq_occ* rank_occ* bol_dict_abc*\n", "\n", "'''\n", "HebrewWordRank_BibleOL_Vocab = BHSa4c.search(HebrewWordRank_BibleOL_Vocab)\n", "BHSa4c.table(HebrewWordRank_BibleOL_Vocab, start=1, end=23, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-05-31T09:06:22.019155Z", "start_time": "2022-05-31T09:06:21.855406Z" } }, "outputs": [], "source": [ "BHSa4c.export(HebrewWordRank_BibleOL_Vocab, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-Personal/4001_publication-presentation/0_pub-book_2023_HebrewVocabBooklet', toFile='HebrewWordRank_BibleOL_Vocab.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T15:37:31.553178Z", "start_time": "2022-03-28T15:37:31.144971Z" } }, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-Personal/4001_publication-presentation/0_pub-book_2023_HebrewVocabBooklet/HebrewWordRank_BibleOL_Vocab.tsv',delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "HebrewWordRank_BibleOL_Vocab.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T15:39:48.194112Z", "start_time": "2022-03-28T15:39:47.998842Z" } }, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab.groupby('lex1').nth((0,1)).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T15:41:02.776881Z", "start_time": "2022-03-28T15:41:02.580566Z" } }, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab=HebrewWordRank_BibleOL_Vocab.groupby('lex1').nth((0,1)).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "HebrewWordRank_BibleOL_Vocab.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-28T15:41:30.939296Z", "start_time": "2022-03-28T15:41:28.815836Z" } }, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-Personal/4001_publication-presentation/0_pub-book_2023_HebrewVocabBooklet/HebrewWordRank_BibleOL_Vocab.xlsx')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Detecting Verbal Forms for BibleOL exercises\n", "## Retrieving the data" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:02:34.115077Z", "start_time": "2022-06-02T20:02:33.132528Z" } }, "outputs": [], "source": [ "## Loading the DataFrame containing all words of the OT\n", "\n", "BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BibleOL_verbal_morphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:02:35.497724Z", "start_time": "2022-06-02T20:02:35.398168Z" } }, "outputs": [], "source": [ "## Selecting only Hebrew words and only verbs\n", "\n", "BibleOL_verbal_morphology = BibleOL_verbal_morphology[(BibleOL_verbal_morphology['pdp1'] == 'verb') \n", " & (BibleOL_verbal_morphology['language1'] == 'Hebrew')]\n", "BibleOL_verbal_morphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:02:39.058935Z", "start_time": "2022-06-02T20:02:39.010455Z" } }, "outputs": [], "source": [ "# For later sorting in excel we need to duplicate important values\n", "\n", "BibleOL_verbal_morphology['bol_language']=BibleOL_verbal_morphology['language1']\n", "BibleOL_verbal_morphology['bol_vc']=BibleOL_verbal_morphology['bol_dict_vc1']\n", "BibleOL_verbal_morphology['bol_vs']=BibleOL_verbal_morphology['vs1']\n", "BibleOL_verbal_morphology['bol_vt']=BibleOL_verbal_morphology['bol_vt1']\n", "BibleOL_verbal_morphology['bol_vc']=BibleOL_verbal_morphology['bol_dict_vc1']\n", "BibleOL_verbal_morphology['bol_ps']=BibleOL_verbal_morphology['ps1']\n", "BibleOL_verbal_morphology['bol_nu']=BibleOL_verbal_morphology['nu1']\n", "BibleOL_verbal_morphology['bol_gn']=BibleOL_verbal_morphology['gn1']\n", "BibleOL_verbal_morphology['bol_nu']=BibleOL_verbal_morphology['nu1']\n", "BibleOL_verbal_morphology['bol_prs_ps']=BibleOL_verbal_morphology['prs_ps1']\n", "BibleOL_verbal_morphology['bol_prs_nu']=BibleOL_verbal_morphology['prs_nu1']\n", "BibleOL_verbal_morphology['bol_prs_gn']=BibleOL_verbal_morphology['prs_gn1']\n", "BibleOL_verbal_morphology['bol_monad_num']=BibleOL_verbal_morphology['bol_monad_num1']\n", "\n", "BibleOL_verbal_morphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:24.065429Z", "start_time": "2022-06-02T20:03:23.931431Z" } }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BibleOL_verbal_morphology_select1=BibleOL_verbal_morphology \\\n", " .groupby(['language1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1']) \\\n", " .nth((0,1)) \\\n", " .sort_values(['bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1',\n", " 'bol_monad_num1'], \n", " ascending=True)\n", "BibleOL_verbal_morphology_select1.head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Preparing the data to allow for proper sorting and sampling" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:34.957890Z", "start_time": "2022-06-02T20:03:34.911505Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphology['vs1'].unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:35.500681Z", "start_time": "2022-06-02T20:03:35.463878Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphology['bol_vt1'].unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:36.390718Z", "start_time": "2022-06-02T20:03:36.354371Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphology['bol_dict_vc1'].unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:43.460205Z", "start_time": "2022-06-02T20:03:43.422874Z" } }, "outputs": [], "source": [ "def sortingaidVC(row):\n", " if row['bol_dict_vc1'] == 'regular':\n", " return '01_regular'\n", " if row['bol_dict_vc1'] == 'i-guttural':\n", " return '02_i-guttural'\n", " if row['bol_dict_vc1'] == 'ii-guttural':\n", " return '03_ii-guttural'\n", " if row['bol_dict_vc1'] == 'iii-guttural':\n", " return '04_iii-guttural'\n", " if row['bol_dict_vc1'] == 'i-aleph':\n", " return '05_i-aleph'\n", " if row['bol_dict_vc1'] == 'iii-aleph':\n", " return '06_iii-aleph'\n", " if row['bol_dict_vc1'] == 'i-nun':\n", " return '07_i-nun'\n", " if row['bol_dict_vc1'] == 'i-waw':\n", " return '08_i-waw'\n", " if row['bol_dict_vc1'] == 'i-yod':\n", " return '09_i-yod'\n", " if row['bol_dict_vc1'] == 'iii-hey':\n", " return '10_iii-hey'\n", " if row['bol_dict_vc1'] == 'ii-waw':\n", " return '11_ii-waw'\n", " if row['bol_dict_vc1'] == 'ii-yod':\n", " return '12_ii-yod'\n", " if row['bol_dict_vc1'] == 'geminate':\n", " return '13_geminate'\n", " else:\n", " return '100'" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:55.594379Z", "start_time": "2022-06-02T20:03:55.558960Z" } }, "outputs": [], "source": [ "def sortingaidVS(row):\n", " if row['vs1'] == 'qal':\n", " return '01_qal'\n", " if row['vs1'] == 'nif':\n", " return '02_nif'\n", " if row['vs1'] == 'piel':\n", " return '03_piel'\n", " if row['vs1'] == 'pual':\n", " return '04_pual'\n", " if row['vs1'] == 'hit':\n", " return '05_hit'\n", " if row['vs1'] == 'hif':\n", " return '06_hif'\n", " if row['vs1'] == 'hof':\n", " return '07_hof'\n", " else:\n", " return '100'" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:56.518324Z", "start_time": "2022-06-02T20:03:56.472636Z" } }, "outputs": [], "source": [ "def sortingaidVT(row):\n", " if row['bol_vt1'] == 'perf':\n", " return '01_perf'\n", " if row['bol_vt1'] == 'impf':\n", " return '02_impf'\n", " if row['bol_vt1'] == 'wayq':\n", " return '03_wayq'\n", " if row['bol_vt1'] == 'coho':\n", " return '04_coho'\n", " if row['bol_vt1'] == 'juss':\n", " return '05_juss'\n", " if row['bol_vt1'] == 'impv':\n", " return '06_impv'\n", " if row['bol_vt1'] == 'infc':\n", " return '07_infc' \n", " if row['bol_vt1'] == 'infa':\n", " return '08_infa'\n", " if row['bol_vt1'] == 'ptca':\n", " return '09_ptca' \n", " if row['bol_vt1'] == 'ptcp':\n", " return '10_ptcp' \n", " else:\n", " return '100'" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:03:58.698605Z", "start_time": "2022-06-02T20:03:58.651211Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphologyOrganized = BibleOL_verbal_morphology\n", "BibleOL_verbal_morphologyOrganized.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:04:02.573889Z", "start_time": "2022-06-02T20:04:02.101325Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphologyOrganized['vs1']=BibleOL_verbal_morphologyOrganized.apply(lambda row : sortingaidVS(row), axis = 1)\n", "BibleOL_verbal_morphologyOrganized.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:04:03.163785Z", "start_time": "2022-06-02T20:04:02.585406Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphologyOrganized['bol_vt1']=BibleOL_verbal_morphologyOrganized.apply(lambda row : sortingaidVT(row), axis = 1)\n", "BibleOL_verbal_morphologyOrganized.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:04:05.758746Z", "start_time": "2022-06-02T20:04:04.704265Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphologyOrganized['bol_dict_vc1']=BibleOL_verbal_morphologyOrganized.apply(lambda row : sortingaidVC(row), axis = 1)\n", "BibleOL_verbal_morphologyOrganized.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:04:11.025932Z", "start_time": "2022-06-02T20:04:10.914718Z" } }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BibleOL_verbal_morphology_select1=BibleOL_verbal_morphologyOrganized \\\n", " .groupby(['language1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1']) \\\n", " .nth((0,1)) \\\n", " .sort_values(['bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1',\n", " 'bol_monad_num1'],\n", " ascending=[True,True,True,True,False,False,True,False,False,True])\n", "BibleOL_verbal_morphology_select1.head(20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T20:04:59.391441Z", "start_time": "2022-06-02T20:04:38.546670Z" } }, "outputs": [], "source": [ "BibleOL_verbal_morphology_select1.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/HebrewVerbalMorphologySelection_2perForm.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Hebrew Vocabulary Builder Statistics by Glanz & Tsegaw\n", "## Loading the Dictionary File" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:50.458029Z", "start_time": "2022-06-24T04:21:48.980512Z" } }, "outputs": [], "source": [ "VocabStats=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/GLI/BibleOL_dictionary_vebal-classes_project/ETCBC4-frequency4.04_progression.xlsx', sheet_name='Hebrew_BibleOL-updated_20210501')\n", "#VocabStats=pd.read_excel('D:/OneDrive - Andrews University/1200_AUS-research/GLI/BibleOL_dictionary_vebal-classes_project/ETCBC4-frequency4.04_progression.xlsx', sheet_name='Hebrew_BibleOL-updated_20210501')\n", "pd.set_option('display.max_columns', 50)\n", "VocabStats.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:51.233953Z", "start_time": "2022-06-24T04:21:51.196393Z" } }, "outputs": [], "source": [ "VocabStats[(VocabStats['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no01')].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True]).count()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Loading BHS Word List" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:54.115814Z", "start_time": "2022-06-24T04:21:53.269903Z" } }, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallWords=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "BHSallWords.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:54.329148Z", "start_time": "2022-06-24T04:21:54.226721Z" } }, "outputs": [], "source": [ "BHSallWordsHebrew = BHSallWords[(BHSallWords['language1'] == 'Hebrew')]\n", "BHSallWordsHebrew.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:55.226054Z", "start_time": "2022-06-24T04:21:55.158010Z" } }, "outputs": [], "source": [ "BHSallWordsHebrew=BHSallWordsHebrew.rename(columns={'lex1':'lex'})\n", "BHSallWordsHebrew.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Adding Section information to BHS Word List" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:58.183533Z", "start_time": "2022-06-24T04:21:57.644311Z" } }, "outputs": [], "source": [ "VocabStatsMerge=pd.merge(BHSallWordsHebrew,VocabStats, on='lex', how='outer')\n", "VocabStatsMerge.sort_values(['R'], ascending=[True]).head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:59.441769Z", "start_time": "2022-06-24T04:21:58.677705Z" } }, "outputs": [], "source": [ "SectionNo1BHS = VocabStatsMerge[\n", " (VocabStatsMerge['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no01')\n", " & (VocabStatsMerge['language1'] == 'Hebrew')\n", "\n", " ].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])\n", "SectionNo1BHS.shape[0]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:59.521026Z", "start_time": "2022-06-24T04:21:59.442762Z" } }, "outputs": [], "source": [ "SectionNo2BHS = VocabStatsMerge[\n", " (VocabStatsMerge['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no02')\n", " & (VocabStatsMerge['language1'] == 'Hebrew')\n", "\n", " ].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])\n", "SectionNo2BHS.shape[0]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:59.584304Z", "start_time": "2022-06-24T04:21:59.522364Z" } }, "outputs": [], "source": [ "SectionNo3BHS = VocabStatsMerge[\n", " (VocabStatsMerge['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no03')\n", " & (VocabStatsMerge['language1'] == 'Hebrew')\n", "\n", " ].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])\n", "SectionNo3BHS.shape[0]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:21:59.945376Z", "start_time": "2022-06-24T04:21:59.870079Z" } }, "outputs": [], "source": [ "SectionNo4BHS = VocabStatsMerge[\n", " (VocabStatsMerge['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no04')\n", " & (VocabStatsMerge['language1'] == 'Hebrew')\n", "\n", " ].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])\n", "SectionNo4BHS.shape[0]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:00.343548Z", "start_time": "2022-06-24T04:22:00.310552Z" } }, "outputs": [], "source": [ "len(SectionNo1BHS)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:00.935447Z", "start_time": "2022-06-24T04:22:00.903606Z" } }, "outputs": [], "source": [ "len(SectionNo2BHS)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:01.306031Z", "start_time": "2022-06-24T04:22:01.277975Z" } }, "outputs": [], "source": [ "len(SectionNo3BHS)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:01.711409Z", "start_time": "2022-06-24T04:22:01.681307Z" } }, "outputs": [], "source": [ "len(SectionNo4BHS)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:02.099016Z", "start_time": "2022-06-24T04:22:02.070765Z" } }, "outputs": [], "source": [ "len(VocabStatsMerge)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Section words in Vocab Booklet" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:03.597962Z", "start_time": "2022-06-24T04:22:03.566307Z" } }, "outputs": [], "source": [ "SectionNo1Booklet=VocabStats[(VocabStats['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no01')].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:04.168191Z", "start_time": "2022-06-24T04:22:04.135707Z" } }, "outputs": [], "source": [ "SectionNo2Booklet=VocabStats[(VocabStats['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no02')].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:06.574959Z", "start_time": "2022-06-24T04:22:06.545441Z" } }, "outputs": [], "source": [ "SectionNo3Booklet=VocabStats[(VocabStats['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no03')].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:07.027365Z", "start_time": "2022-06-24T04:22:06.994508Z" } }, "outputs": [], "source": [ "SectionNo4Booklet=VocabStats[(VocabStats['BiblicalHebrewVocabularyBuilderSection'] == 'Section_no04')].sort_values(['BiblicalHebrewVocabularyBuilderSection'], ascending=[True])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:08.075689Z", "start_time": "2022-06-24T04:22:08.041820Z" } }, "outputs": [], "source": [ "len(SectionNo1Booklet)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:08.424932Z", "start_time": "2022-06-24T04:22:08.393446Z" } }, "outputs": [], "source": [ "len(SectionNo2Booklet)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:08.826861Z", "start_time": "2022-06-24T04:22:08.796281Z" } }, "outputs": [], "source": [ "len(SectionNo3Booklet)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:09.259718Z", "start_time": "2022-06-24T04:22:09.229768Z" } }, "outputs": [], "source": [ "len(SectionNo4Booklet)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Presentable Calculations for Booklet" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:11.065143Z", "start_time": "2022-06-24T04:22:11.030007Z" } }, "outputs": [], "source": [ "HowManySectionNo1WordsInBHS = 100/len(VocabStatsMerge)*len(SectionNo1BHS)\n", "HowManySectionNo1WordsInBHS" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:11.957960Z", "start_time": "2022-06-24T04:22:11.926554Z" } }, "outputs": [], "source": [ "HowManySectionNo2WordsInBHS = 100/len(VocabStatsMerge)*len(SectionNo2BHS)\n", "HowManySectionNo2WordsInBHS" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:12.419464Z", "start_time": "2022-06-24T04:22:12.388351Z" } }, "outputs": [], "source": [ "HowManySectionNo3WordsInBHS = 100/len(VocabStatsMerge)*len(SectionNo3BHS)\n", "HowManySectionNo3WordsInBHS" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:12.886376Z", "start_time": "2022-06-24T04:22:12.857112Z" } }, "outputs": [], "source": [ "HowManySectionNo4WordsInBHS = 100/len(VocabStatsMerge)*len(SectionNo4BHS)\n", "HowManySectionNo4WordsInBHS" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:13.716197Z", "start_time": "2022-06-24T04:22:13.684913Z" } }, "outputs": [], "source": [ "x = HowManySectionNo1WordsInBHS + HowManySectionNo2WordsInBHS\n", "x" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:14.226198Z", "start_time": "2022-06-24T04:22:14.196614Z" } }, "outputs": [], "source": [ "x = HowManySectionNo1WordsInBHS + HowManySectionNo2WordsInBHS + HowManySectionNo3WordsInBHS\n", "x" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:15.559436Z", "start_time": "2022-06-24T04:22:15.527485Z" } }, "outputs": [], "source": [ "x = HowManySectionNo1WordsInBHS + HowManySectionNo2WordsInBHS + HowManySectionNo3WordsInBHS + HowManySectionNo4WordsInBHS\n", "x" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:17.132870Z", "start_time": "2022-06-24T04:22:16.910404Z" } }, "outputs": [], "source": [ "VocabStatsMerge.groupby(['BiblicalHebrewVocabularyBuilderSection']).sum().plot(kind='pie', y='R', subplots=True, shadow = True,startangle=45,figsize=(15,10), autopct='%1.1f%%')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:22:23.143889Z", "start_time": "2022-06-24T04:22:23.107208Z" } }, "outputs": [], "source": [ "from matplotlib import pyplot as plt\n", "import numpy as np\n", "\n", "#https://www.geeksforgeeks.org/how-to-plot-a-pandas-dataframe-with-matplotlib/\n", "#https://www.geeksforgeeks.org/plot-a-pie-chart-in-python-using-matplotlib/" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:28:18.822495Z", "start_time": "2022-06-24T04:28:18.718161Z" } }, "outputs": [], "source": [ "VocabStatsMerge.BiblicalHebrewVocabularyBuilderSection.value_counts(sort=False).plot.pie(autopct='%1.1f%%', shadow=True, startangle=45)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:25:06.221814Z", "start_time": "2022-06-24T04:25:06.070645Z" } }, "outputs": [], "source": [ "plt.pie(VocabStatsMerge[\"R\"], labels=VocabStatsMerge.groupby(['BiblicalHebrewVocabularyBuilderSection']).sum())\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-24T04:23:45.737549Z", "start_time": "2022-06-24T04:23:45.662358Z" } }, "outputs": [], "source": [ "df = pd.DataFrame({\n", " 'Object': ['Bulb', 'Lamp', 'Table', 'Pen', 'Notebook'],\n", " 'Price': [45, 38, 90, 60, 40]\n", "})\n", " \n", "# plotting a pie chart\n", "plt.pie(df[\"Price\"], labels=df[\"Object\"])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Irregular Noun Construct retrieval" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T16:50:35.013412Z", "start_time": "2022-08-14T16:50:33.826131Z" } }, "outputs": [], "source": [ "IrregularNouns1='''\n", "word g_word_noaccent g_word_utf8_noaccent g_lex_utf8 voc_lex_utf8 lex bol_dict_HebArm sp=subs nu=pl st=a prs_ps#p1|p2|p3 language=Hebrew\n", "'''\n", "IrregularNouns1 = BHSa4c.search(IrregularNouns1)\n", "BHSa4c.show(IrregularNouns1, start=1, end=23, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T16:50:41.226511Z", "start_time": "2022-08-14T16:50:40.805018Z" } }, "outputs": [], "source": [ "BHSa4c.export(IrregularNouns1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew', toFile='IrregularNouns_pl-abs.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T16:50:54.398880Z", "start_time": "2022-08-14T16:50:53.013047Z" } }, "outputs": [], "source": [ "IrregularNouns2='''\n", "word lex g_word_noaccent g_word_utf8_noaccent g_lex_utf8 voc_lex_utf8 bol_dict_HebArm sp=subs nu=sg st=c prs_ps#p1|p2|p3 language=Hebrew\n", "'''\n", "IrregularNouns2 = BHSa4c.search(IrregularNouns2)\n", "BHSa4c.show(IrregularNouns2, start=1, end=23, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T16:50:56.024567Z", "start_time": "2022-08-14T16:50:55.398720Z" } }, "outputs": [], "source": [ "BHSa4c.export(IrregularNouns2, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew', toFile='IrregularNouns_sg-cs.tsv')" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2022-08-14T13:21:28.696335Z", "start_time": "2022-08-14T13:21:28.664959Z" } }, "source": [ "# Piroritized stems for Verbs" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T17:57:22.470876Z", "start_time": "2022-08-14T17:57:21.361857Z" } }, "outputs": [], "source": [ "VerbalStemsPririty='''\n", "word sp=verb lex bol_dict_HebArm language=Hebrew vs bol_fa_order bol_lex_occ bol_dict_abc\n", "'''\n", "VerbalStemsPririty = BHSa4c.search(VerbalStemsPririty)\n", "BHSa4c.table(VerbalStemsPririty, start=1, end=10, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T17:57:25.155312Z", "start_time": "2022-08-14T17:57:23.789253Z" } }, "outputs": [], "source": [ "BHSa4c.export(VerbalStemsPririty, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew', toFile='BHSa4c_verbal_stem-priority.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T19:03:50.155741Z", "start_time": "2022-08-14T19:03:50.015666Z" } }, "outputs": [], "source": [ "stempriority=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_verbal_stem-priority.tsv', delimiter='\\t',encoding='utf-16')\n", "pd.set_option('display.max_columns', 50)\n", "stempriority.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T19:03:50.908663Z", "start_time": "2022-08-14T19:03:50.869548Z" } }, "outputs": [], "source": [ "pd.set_option('display.max_rows', 20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T19:15:00.215928Z", "start_time": "2022-08-14T19:15:00.138164Z" } }, "outputs": [], "source": [ "stempriority.groupby(['bol_dict_HebArm1','bol_fa_order1','vs1']).count().sort_values(['bol_fa_order1','R', 'vs1',], ascending=[True,False,True])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T19:15:19.038853Z", "start_time": "2022-08-14T19:15:18.970678Z" } }, "outputs": [], "source": [ "stempriorityexport=stempriority.groupby(['bol_dict_HebArm1','bol_fa_order1','vs1']).count().sort_values(['bol_fa_order1','R', 'vs1',], ascending=[True,False,True])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-08-14T19:15:23.196723Z", "start_time": "2022-08-14T19:15:19.856041Z" } }, "outputs": [], "source": [ "stempriorityexport.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/stempriority2.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Hebrew Qualifier\n", "The following texts are being used by the OTST teachers:\n", "\n", "Genesis:1, 3, 6, 12, 13, 18, 19, 20, 21, 22, 25, 26\n", "\n", "Exodus: 20\n", "\n", "Joshua:10\n", "\n", "Judges: 19\n", "\n", "1 Samuel: 1\n", "\n", "2 Kings: 6\n", "\n", "Ruth: 1, 2, \n", "\n", "Jeremiah: 37, 38, 39\n", "\n", "Psalms: 1, 3\n", "\n", "Jonah: 1\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Vocab\n", "### Getting the vocab for Hebrew-I, Hebrew-II, Hebrew-III" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "HebrewWordRank_BibleOL_Vocab='''\n", "word lex* bol_dict_HebArm* bol_dict_EN number* g_word_noaccent* freq_occ* rank_occ* bol_fa_order* bol_dict_vc* sp* bol_lexeme_occurrences* bol_dict_abc* language* bol_monad_num* qere_utf8* g_word_utf8* g_lex_utf8* bol_g_word_utf8* bol_qere_presence*\n", "\n", "'''\n", "HebrewWordRank_BibleOL_Vocab = BHSa4c.search(HebrewWordRank_BibleOL_Vocab)\n", "BHSa4c.table(HebrewWordRank_BibleOL_Vocab, start=1, end=5, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(HebrewWordRank_BibleOL_Vocab, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises', toFile='BHSa4c_BOL_vocab_exercises_HebI-II-III.tsv')" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
01Genesis111wordבְּin, at (time, place); with; by; by means ofבְּ834NaN4בְּ155411014194בְּB.:-בְּHebrewB1NaN3prep
12Genesis112wordרֵאשִׁ֖יתbeginning, firstרֵאשִׁית7117NaN716רֵאשִׁ֖ית512045רֵאשִׁיתR;>CIJTרֵאשִׁ֖יתHebrewR>CJT/2NaN868subs
23Genesis113wordבָּרָ֣אqal: create; ni: be created;ברא I1188ii-guttural, iii-aleph748בָּרָ֣א483015בָּרָאB.@R@>בָּרָ֣אHebrewBR>[3NaN2341verb
34Genesis114wordאֱלֹהִ֑יםGod; gods; godאֱלֹהִים412NaN19אֱלֹהִ֑ים2601401177אֱלֹה>:ELOHIJMאֱלֹהִ֑יםHebrew>LHJM/4NaN31subs
45Genesis115wordאֵ֥ת<OM>; object markerאֵת I815NaN5אֵ֥ת11016509743אֵת>;Tאֵ֥תHebrew>T5NaN4prep
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 1 Genesis 1 1 1 word בְּ \n", "1 2 Genesis 1 1 2 word רֵאשִׁ֖ית \n", "2 3 Genesis 1 1 3 word בָּרָ֣א \n", "3 4 Genesis 1 1 4 word אֱלֹהִ֑ים \n", "4 5 Genesis 1 1 5 word אֵ֥ת \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 in, at (time, place); with; by; by means of בְּ \n", "1 beginning, first רֵאשִׁית \n", "2 qal: create; ni: be created; ברא I \n", "3 God; gods; god אֱלֹהִים \n", "4 ; object marker אֵת I \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 \\\n", "0 834 NaN 4 בְּ \n", "1 7117 NaN 716 רֵאשִׁ֖ית \n", "2 1188 ii-guttural, iii-aleph 748 בָּרָ֣א \n", "3 412 NaN 19 אֱלֹהִ֑ים \n", "4 815 NaN 5 אֵ֥ת \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 freq_occ1 \\\n", "0 15541 1 0 14194 \n", "1 51 2 0 45 \n", "2 48 3 0 15 \n", "3 2601 4 0 1177 \n", "4 11016 5 0 9743 \n", "\n", " g_lex_utf81 g_word_noaccent1 g_word_utf81 language1 lex1 number1 \\\n", "0 בְּ B.:- בְּ Hebrew B 1 \n", "1 רֵאשִׁית R;>CIJT רֵאשִׁ֖ית Hebrew R>CJT/ 2 \n", "2 בָּרָא B.@R@> בָּרָ֣א Hebrew BR>[ 3 \n", "3 אֱלֹה >:ELOHIJM אֱלֹהִ֑ים Hebrew >LHJM/ 4 \n", "4 אֵת >;T אֵ֥ת Hebrew >T 5 \n", "\n", " qere_utf81 rank_occ1 sp1 \n", "0 NaN 3 prep \n", "1 NaN 868 subs \n", "2 NaN 2341 verb \n", "3 NaN 31 subs \n", "4 NaN 4 prep " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallWords=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_vocab_exercises_HebI-II-III.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "BHSallWords.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST551 Vocab" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
01Genesis111wordבְּin, at (time, place); with; by; by means ofבְּ834NaN4בְּ155411014194בְּB.:-בְּHebrewB1NaN3prep
34Genesis114wordאֱלֹהִ֑יםGod; gods; godאֱלֹהִים412NaN19אֱלֹהִ֑ים2601401177אֱלֹה>:ELOHIJMאֱלֹהִ֑יםHebrew>LHJM/4NaN31subs
45Genesis115wordאֵ֥ת<OM>; object markerאֵת I815NaN5אֵ֥ת11016509743אֵת>;Tאֵ֥תHebrew>T5NaN4prep
56Genesis116wordהַthe (art)הַ I1792NaN2הַ303806024664הַHA-הַHebrewH6NaN1art
67Genesis117wordשָּׁמַ֖יִםheaven; skyשָׁמַיִם7832NaN123שָּׁמַ֖יִם42170395שָּׁמַיC.@MAJIMשָּׁמַ֖יִםHebrewCMJM/7NaN85subs
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 1 Genesis 1 1 1 word בְּ \n", "3 4 Genesis 1 1 4 word אֱלֹהִ֑ים \n", "4 5 Genesis 1 1 5 word אֵ֥ת \n", "5 6 Genesis 1 1 6 word הַ \n", "6 7 Genesis 1 1 7 word שָּׁמַ֖יִם \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 in, at (time, place); with; by; by means of בְּ \n", "3 God; gods; god אֱלֹהִים \n", "4 ; object marker אֵת I \n", "5 the (art) הַ I \n", "6 heaven; sky שָׁמַיִם \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 \\\n", "0 834 NaN 4 בְּ \n", "3 412 NaN 19 אֱלֹהִ֑ים \n", "4 815 NaN 5 אֵ֥ת \n", "5 1792 NaN 2 הַ \n", "6 7832 NaN 123 שָּׁמַ֖יִם \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 freq_occ1 \\\n", "0 15541 1 0 14194 \n", "3 2601 4 0 1177 \n", "4 11016 5 0 9743 \n", "5 30380 6 0 24664 \n", "6 421 7 0 395 \n", "\n", " g_lex_utf81 g_word_noaccent1 g_word_utf81 language1 lex1 number1 \\\n", "0 בְּ B.:- בְּ Hebrew B 1 \n", "3 אֱלֹה >:ELOHIJM אֱלֹהִ֑ים Hebrew >LHJM/ 4 \n", "4 אֵת >;T אֵ֥ת Hebrew >T 5 \n", "5 הַ HA- הַ Hebrew H 6 \n", "6 שָּׁמַי C.@MAJIM שָּׁמַ֖יִם Hebrew CMJM/ 7 \n", "\n", " qere_utf81 rank_occ1 sp1 \n", "0 NaN 3 prep \n", "3 NaN 31 subs \n", "4 NaN 4 prep \n", "5 NaN 1 art \n", "6 NaN 85 subs " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST551=BHSallWords[(BHSallWords['language1']=='Hebrew') \n", " & (BHSallWords['bol_lexeme_occurrences1']>=200)\n", " & (~BHSallWords['g_word_noaccent1'].astype(str).str.contains(\"^\\*\"))\n", " & (~BHSallWords['bol_dict_vc1'].astype(str).str.contains(\"four.*verb\"))\n", "\n", " ]\n", "BHSallHebrewWords_OTST551.head() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Random Selection `sample` " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
1676651676662_Samuel1324167666wordוַand; also, even (conj); butוְ1952NaN1וַ50273167665050238וַWA-וַHebrewW7201NaN0conj
348915348916Proverbs89348916wordוִֽ֝and; also, even (conj); butוְ1952NaN1וִֽ֝50273348915050238וִWI-וִֽ֝HebrewW1984NaN0conj
379264379265Ezra37379265wordוְand; also, even (conj); butוְ1952NaN1וְ50273379264050238וְW:-וְHebrewW1119NaN0conj
1812601812611_Kings719181261wordהָthe (art)הַ I1792NaN2הָ30380181260024664הָH@-הָHebrewH5184NaN1art
50105011Genesis1135011wordהַ֣the (art)הַ I1792NaN2הַ֣303805011024664הַHA-הַ֣HebrewH5011NaN1art
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "167665 167666 2_Samuel 13 24 167666 word וַ \n", "348915 348916 Proverbs 8 9 348916 word וִֽ֝ \n", "379264 379265 Ezra 3 7 379265 word וְ \n", "181260 181261 1_Kings 7 19 181261 word הָ \n", "5010 5011 Genesis 11 3 5011 word הַ֣ \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 bol_dict_abc1 \\\n", "167665 and; also, even (conj); but וְ 1952 \n", "348915 and; also, even (conj); but וְ 1952 \n", "379264 and; also, even (conj); but וְ 1952 \n", "181260 the (art) הַ I 1792 \n", "5010 the (art) הַ I 1792 \n", "\n", " bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "167665 NaN 1 וַ 50273 \n", "348915 NaN 1 וִֽ֝ 50273 \n", "379264 NaN 1 וְ 50273 \n", "181260 NaN 2 הָ 30380 \n", "5010 NaN 2 הַ֣ 30380 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "167665 167665 0 50238 וַ \n", "348915 348915 0 50238 וִ \n", "379264 379264 0 50238 וְ \n", "181260 181260 0 24664 הָ \n", "5010 5011 0 24664 הַ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 qere_utf81 \\\n", "167665 WA- וַ Hebrew W 7201 NaN \n", "348915 WI- וִֽ֝ Hebrew W 1984 NaN \n", "379264 W:- וְ Hebrew W 1119 NaN \n", "181260 H@- הָ Hebrew H 5184 NaN \n", "5010 HA- הַ֣ Hebrew H 5011 NaN \n", "\n", " rank_occ1 sp1 \n", "167665 0 conj \n", "348915 0 conj \n", "379264 0 conj \n", "181260 1 art \n", "5010 1 art " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST551_selection_of_random3=BHSallHebrewWords_OTST551.groupby('bol_dict_HebArm1').sample(n=3, replace=True).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "BHSallHebrewWords_OTST551_selection_of_random3.head()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
1676651676662_Samuel1324167666wordוַand; also, even (conj); butוְ1952NaN1וַ50273167665050238וַWA-וַHebrewW7201NaN0conj
348915348916Proverbs89348916wordוִֽ֝and; also, even (conj); butוְ1952NaN1וִֽ֝50273348915050238וִWI-וִֽ֝HebrewW1984NaN0conj
379264379265Ezra37379265wordוְand; also, even (conj); butוְ1952NaN1וְ50273379264050238וְW:-וְHebrewW1119NaN0conj
1812601812611_Kings719181261wordהָthe (art)הַ I1792NaN2הָ30380181260024664הָH@-הָHebrewH5184NaN1art
50105011Genesis1135011wordהַ֣the (art)הַ I1792NaN2הַ֣303805011024664הַHA-הַ֣HebrewH5011NaN1art
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "167665 167666 2_Samuel 13 24 167666 word וַ \n", "348915 348916 Proverbs 8 9 348916 word וִֽ֝ \n", "379264 379265 Ezra 3 7 379265 word וְ \n", "181260 181261 1_Kings 7 19 181261 word הָ \n", "5010 5011 Genesis 11 3 5011 word הַ֣ \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 bol_dict_abc1 \\\n", "167665 and; also, even (conj); but וְ 1952 \n", "348915 and; also, even (conj); but וְ 1952 \n", "379264 and; also, even (conj); but וְ 1952 \n", "181260 the (art) הַ I 1792 \n", "5010 the (art) הַ I 1792 \n", "\n", " bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "167665 NaN 1 וַ 50273 \n", "348915 NaN 1 וִֽ֝ 50273 \n", "379264 NaN 1 וְ 50273 \n", "181260 NaN 2 הָ 30380 \n", "5010 NaN 2 הַ֣ 30380 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "167665 167665 0 50238 וַ \n", "348915 348915 0 50238 וִ \n", "379264 379264 0 50238 וְ \n", "181260 181260 0 24664 הָ \n", "5010 5011 0 24664 הַ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 qere_utf81 \\\n", "167665 WA- וַ Hebrew W 7201 NaN \n", "348915 WI- וִֽ֝ Hebrew W 1984 NaN \n", "379264 W:- וְ Hebrew W 1119 NaN \n", "181260 H@- הָ Hebrew H 5184 NaN \n", "5010 HA- הַ֣ Hebrew H 5011 NaN \n", "\n", " rank_occ1 sp1 \n", "167665 0 conj \n", "348915 0 conj \n", "379264 0 conj \n", "181260 1 art \n", "5010 1 art " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST551_selection_of_random3.drop_duplicates(subset=\"bol_monad_num1\", keep='first', inplace=True)\n", "BHSallHebrewWords_OTST551_selection_of_random3.head(5)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords_OTST551_selection_of_random3.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_vocab_OTST_551_Qualifier-Selection_unfiltered_0.3.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST552 Vocab" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
01Genesis111wordבְּin, at (time, place); with; by; by means ofבְּ834NaN4בְּ155411014194בְּB.:-בְּHebrewB1NaN3prep
34Genesis114wordאֱלֹהִ֑יםGod; gods; godאֱלֹהִים412NaN19אֱלֹהִ֑ים2601401177אֱלֹה>:ELOHIJMאֱלֹהִ֑יםHebrew>LHJM/4NaN31subs
45Genesis115wordאֵ֥ת<OM>; object markerאֵת I815NaN5אֵ֥ת11016509743אֵת>;Tאֵ֥תHebrew>T5NaN4prep
56Genesis116wordהַthe (art)הַ I1792NaN2הַ303806024664הַHA-הַHebrewH6NaN1art
67Genesis117wordשָּׁמַ֖יִםheaven; skyשָׁמַיִם7832NaN123שָּׁמַ֖יִם42170395שָּׁמַיC.@MAJIMשָּׁמַ֖יִםHebrewCMJM/7NaN85subs
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 1 Genesis 1 1 1 word בְּ \n", "3 4 Genesis 1 1 4 word אֱלֹהִ֑ים \n", "4 5 Genesis 1 1 5 word אֵ֥ת \n", "5 6 Genesis 1 1 6 word הַ \n", "6 7 Genesis 1 1 7 word שָּׁמַ֖יִם \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 in, at (time, place); with; by; by means of בְּ \n", "3 God; gods; god אֱלֹהִים \n", "4 ; object marker אֵת I \n", "5 the (art) הַ I \n", "6 heaven; sky שָׁמַיִם \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 \\\n", "0 834 NaN 4 בְּ \n", "3 412 NaN 19 אֱלֹהִ֑ים \n", "4 815 NaN 5 אֵ֥ת \n", "5 1792 NaN 2 הַ \n", "6 7832 NaN 123 שָּׁמַ֖יִם \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 freq_occ1 \\\n", "0 15541 1 0 14194 \n", "3 2601 4 0 1177 \n", "4 11016 5 0 9743 \n", "5 30380 6 0 24664 \n", "6 421 7 0 395 \n", "\n", " g_lex_utf81 g_word_noaccent1 g_word_utf81 language1 lex1 number1 \\\n", "0 בְּ B.:- בְּ Hebrew B 1 \n", "3 אֱלֹה >:ELOHIJM אֱלֹהִ֑ים Hebrew >LHJM/ 4 \n", "4 אֵת >;T אֵ֥ת Hebrew >T 5 \n", "5 הַ HA- הַ Hebrew H 6 \n", "6 שָּׁמַי C.@MAJIM שָּׁמַ֖יִם Hebrew CMJM/ 7 \n", "\n", " qere_utf81 rank_occ1 sp1 \n", "0 NaN 3 prep \n", "3 NaN 31 subs \n", "4 NaN 4 prep \n", "5 NaN 1 art \n", "6 NaN 85 subs " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST552=BHSallWords[(BHSallWords['language1']=='Hebrew') \n", " & (BHSallWords['bol_lexeme_occurrences1']>=100)\n", " & (~BHSallWords['g_word_noaccent1'].astype(str).str.contains(\"^\\*\"))\n", " & (~BHSallWords['bol_dict_vc1'].astype(str).str.contains(\"four.*verb\"))\n", "\n", " ]\n", "BHSallHebrewWords_OTST552.head() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sequenced Selection with `nth` " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
bol_dict_HebArm1
וְ8Genesis118wordוְand; also, even (conj); but1952NaN1וְ502738050238וְW:-וְHebrewW8NaN0conj
וְ17Genesis1217wordוָand; also, even (conj); but1952NaN1וָ5027317050238וָW@-וָHebrewW17NaN0conj
וְ12Genesis1212wordוְand; also, even (conj); but1952NaN1וְ5027312050238וְW:-וְHebrewW12NaN0conj
הַ I13Genesis1213wordהָthe (art)1792NaN2הָ3038013024664הָH@-הָHebrewH13NaN1art
הַ I6Genesis116wordהַthe (art)1792NaN2הַ303806024664הַHA-הַHebrewH6NaN1art
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "bol_dict_HebArm1 \n", "וְ 8 Genesis 1 1 8 word וְ \n", "וְ 17 Genesis 1 2 17 word וָ \n", "וְ 12 Genesis 1 2 12 word וְ \n", "הַ I 13 Genesis 1 2 13 word הָ \n", "הַ I 6 Genesis 1 1 6 word הַ \n", "\n", " bol_dict_EN1 bol_dict_abc1 bol_dict_vc1 \\\n", "bol_dict_HebArm1 \n", "וְ and; also, even (conj); but 1952 NaN \n", "וְ and; also, even (conj); but 1952 NaN \n", "וְ and; also, even (conj); but 1952 NaN \n", "הַ I the (art) 1792 NaN \n", "הַ I the (art) 1792 NaN \n", "\n", " bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "bol_dict_HebArm1 \n", "וְ 1 וְ 50273 \n", "וְ 1 וָ 50273 \n", "וְ 1 וְ 50273 \n", "הַ I 2 הָ 30380 \n", "הַ I 2 הַ 30380 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "bol_dict_HebArm1 \n", "וְ 8 0 50238 וְ \n", "וְ 17 0 50238 וָ \n", "וְ 12 0 50238 וְ \n", "הַ I 13 0 24664 הָ \n", "הַ I 6 0 24664 הַ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 \\\n", "bol_dict_HebArm1 \n", "וְ W:- וְ Hebrew W 8 \n", "וְ W@- וָ Hebrew W 17 \n", "וְ W:- וְ Hebrew W 12 \n", "הַ I H@- הָ Hebrew H 13 \n", "הַ I HA- הַ Hebrew H 6 \n", "\n", " qere_utf81 rank_occ1 sp1 \n", "bol_dict_HebArm1 \n", "וְ NaN 0 conj \n", "וְ NaN 0 conj \n", "וְ NaN 0 conj \n", "הַ I NaN 1 art \n", "הַ I NaN 1 art " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST552_nth3=BHSallHebrewWords_OTST552.groupby('bol_dict_HebArm1').nth((0,1,2)).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "BHSallHebrewWords_OTST552_nth3.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Random Selection `sample` " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
1517841517851_Samuel1744151785wordוְand; also, even (conj); butוְ1952NaN1וְ50273151784050238וְW:-וְHebrewW10249NaN0conj
127476127477Judges12127477wordוַand; also, even (conj); butוְ1952NaN1וַ50273127476050238וַWA-וַHebrewW26NaN0conj
8112181122Numbers172081122wordוְand; also, even (conj); butוְ1952NaN1וְ5027381121050238וְW:-וְHebrewW11512NaN0conj
337237337238Job417337238wordהַֽ֭<IH>, interrogative Heהֲ II1793NaN72הַֽ֭743337237024664הַHA-הַֽ֭HebrewH=1218NaN1inrg
224024224025Isaiah3612224025wordהֲ<IH>, interrogative Heהֲ II1793NaN72הֲ743224024024664הֲH:A-הֲHebrewH=11956NaN1inrg
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "151784 151785 1_Samuel 17 44 151785 word וְ \n", "127476 127477 Judges 1 2 127477 word וַ \n", "81121 81122 Numbers 17 20 81122 word וְ \n", "337237 337238 Job 4 17 337238 word הַֽ֭ \n", "224024 224025 Isaiah 36 12 224025 word הֲ \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 bol_dict_abc1 \\\n", "151784 and; also, even (conj); but וְ 1952 \n", "127476 and; also, even (conj); but וְ 1952 \n", "81121 and; also, even (conj); but וְ 1952 \n", "337237 , interrogative He הֲ II 1793 \n", "224024 , interrogative He הֲ II 1793 \n", "\n", " bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "151784 NaN 1 וְ 50273 \n", "127476 NaN 1 וַ 50273 \n", "81121 NaN 1 וְ 50273 \n", "337237 NaN 72 הַֽ֭ 743 \n", "224024 NaN 72 הֲ 743 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "151784 151784 0 50238 וְ \n", "127476 127476 0 50238 וַ \n", "81121 81121 0 50238 וְ \n", "337237 337237 0 24664 הַ \n", "224024 224024 0 24664 הֲ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 qere_utf81 \\\n", "151784 W:- וְ Hebrew W 10249 NaN \n", "127476 WA- וַ Hebrew W 26 NaN \n", "81121 W:- וְ Hebrew W 11512 NaN \n", "337237 HA- הַֽ֭ Hebrew H= 1218 NaN \n", "224024 H:A- הֲ Hebrew H= 11956 NaN \n", "\n", " rank_occ1 sp1 \n", "151784 0 conj \n", "127476 0 conj \n", "81121 0 conj \n", "337237 1 inrg \n", "224024 1 inrg " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST552_selection_of_random3=BHSallHebrewWords_OTST552.groupby('bol_dict_HebArm1').sample(n=3, replace=True).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "BHSallHebrewWords_OTST552_selection_of_random3.head()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
1517841517851_Samuel1744151785wordוְand; also, even (conj); butוְ1952NaN1וְ50273151784050238וְW:-וְHebrewW10249NaN0conj
127476127477Judges12127477wordוַand; also, even (conj); butוְ1952NaN1וַ50273127476050238וַWA-וַHebrewW26NaN0conj
8112181122Numbers172081122wordוְand; also, even (conj); butוְ1952NaN1וְ5027381121050238וְW:-וְHebrewW11512NaN0conj
337237337238Job417337238wordהַֽ֭<IH>, interrogative Heהֲ II1793NaN72הַֽ֭743337237024664הַHA-הַֽ֭HebrewH=1218NaN1inrg
224024224025Isaiah3612224025wordהֲ<IH>, interrogative Heהֲ II1793NaN72הֲ743224024024664הֲH:A-הֲHebrewH=11956NaN1inrg
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "151784 151785 1_Samuel 17 44 151785 word וְ \n", "127476 127477 Judges 1 2 127477 word וַ \n", "81121 81122 Numbers 17 20 81122 word וְ \n", "337237 337238 Job 4 17 337238 word הַֽ֭ \n", "224024 224025 Isaiah 36 12 224025 word הֲ \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 bol_dict_abc1 \\\n", "151784 and; also, even (conj); but וְ 1952 \n", "127476 and; also, even (conj); but וְ 1952 \n", "81121 and; also, even (conj); but וְ 1952 \n", "337237 , interrogative He הֲ II 1793 \n", "224024 , interrogative He הֲ II 1793 \n", "\n", " bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "151784 NaN 1 וְ 50273 \n", "127476 NaN 1 וַ 50273 \n", "81121 NaN 1 וְ 50273 \n", "337237 NaN 72 הַֽ֭ 743 \n", "224024 NaN 72 הֲ 743 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "151784 151784 0 50238 וְ \n", "127476 127476 0 50238 וַ \n", "81121 81121 0 50238 וְ \n", "337237 337237 0 24664 הַ \n", "224024 224024 0 24664 הֲ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 qere_utf81 \\\n", "151784 W:- וְ Hebrew W 10249 NaN \n", "127476 WA- וַ Hebrew W 26 NaN \n", "81121 W:- וְ Hebrew W 11512 NaN \n", "337237 HA- הַֽ֭ Hebrew H= 1218 NaN \n", "224024 H:A- הֲ Hebrew H= 11956 NaN \n", "\n", " rank_occ1 sp1 \n", "151784 0 conj \n", "127476 0 conj \n", "81121 0 conj \n", "337237 1 inrg \n", "224024 1 inrg " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST552_selection_of_random3.drop_duplicates(subset=\"bol_monad_num1\", keep='first', inplace=True)\n", "BHSallHebrewWords_OTST552_selection_of_random3.head(5)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords_OTST552_selection_of_random3.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_vocab_OTST_552_Qualifier-Selection_unfiltered_0.3.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### OTST625 Vocab" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
01Genesis111wordבְּin, at (time, place); with; by; by means ofבְּ834NaN4בְּ155411014194בְּB.:-בְּHebrewB1NaN3prep
34Genesis114wordאֱלֹהִ֑יםGod; gods; godאֱלֹהִים412NaN19אֱלֹהִ֑ים2601401177אֱלֹה>:ELOHIJMאֱלֹהִ֑יםHebrew>LHJM/4NaN31subs
45Genesis115wordאֵ֥ת<OM>; object markerאֵת I815NaN5אֵ֥ת11016509743אֵת>;Tאֵ֥תHebrew>T5NaN4prep
56Genesis116wordהַthe (art)הַ I1792NaN2הַ303806024664הַHA-הַHebrewH6NaN1art
67Genesis117wordשָּׁמַ֖יִםheaven; skyשָׁמַיִם7832NaN123שָּׁמַ֖יִם42170395שָּׁמַיC.@MAJIMשָּׁמַ֖יִםHebrewCMJM/7NaN85subs
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 1 Genesis 1 1 1 word בְּ \n", "3 4 Genesis 1 1 4 word אֱלֹהִ֑ים \n", "4 5 Genesis 1 1 5 word אֵ֥ת \n", "5 6 Genesis 1 1 6 word הַ \n", "6 7 Genesis 1 1 7 word שָּׁמַ֖יִם \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 in, at (time, place); with; by; by means of בְּ \n", "3 God; gods; god אֱלֹהִים \n", "4 ; object marker אֵת I \n", "5 the (art) הַ I \n", "6 heaven; sky שָׁמַיִם \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 \\\n", "0 834 NaN 4 בְּ \n", "3 412 NaN 19 אֱלֹהִ֑ים \n", "4 815 NaN 5 אֵ֥ת \n", "5 1792 NaN 2 הַ \n", "6 7832 NaN 123 שָּׁמַ֖יִם \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 freq_occ1 \\\n", "0 15541 1 0 14194 \n", "3 2601 4 0 1177 \n", "4 11016 5 0 9743 \n", "5 30380 6 0 24664 \n", "6 421 7 0 395 \n", "\n", " g_lex_utf81 g_word_noaccent1 g_word_utf81 language1 lex1 number1 \\\n", "0 בְּ B.:- בְּ Hebrew B 1 \n", "3 אֱלֹה >:ELOHIJM אֱלֹהִ֑ים Hebrew >LHJM/ 4 \n", "4 אֵת >;T אֵ֥ת Hebrew >T 5 \n", "5 הַ HA- הַ Hebrew H 6 \n", "6 שָּׁמַי C.@MAJIM שָּׁמַ֖יִם Hebrew CMJM/ 7 \n", "\n", " qere_utf81 rank_occ1 sp1 \n", "0 NaN 3 prep \n", "3 NaN 31 subs \n", "4 NaN 4 prep \n", "5 NaN 1 art \n", "6 NaN 85 subs " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST625=BHSallWords[(BHSallWords['language1']=='Hebrew') \n", " & (BHSallWords['bol_lexeme_occurrences1']>=70)\n", " & (~BHSallWords['g_word_noaccent1'].astype(str).str.contains(\"^\\*\"))\n", " & (~BHSallWords['bol_dict_vc1'].astype(str).str.contains(\"four.*verb\"))\n", "\n", " ]\n", "BHSallHebrewWords_OTST625.head() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Random Selection `sample` " ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
362447362448Ecclesiastes95362448wordוְand; also, even (conj); butוְ1952NaN1וְ50273362447050238וְW:-וְHebrewW3173NaN0conj
4143244143252_Chronicles165414325wordוַand; also, even (conj); butוְ1952NaN1וַ50273414324050238וַWA-וַHebrewW7505NaN0conj
383061383062Ezra1014383062wordוְand; also, even (conj); butוְ1952NaN1וְ50273383061050238וְW:-וְHebrewW4916NaN0conj
1531051531061_Samuel1911153106wordהַthe (art)הַ I1792NaN2הַ30380153105024664הַHA-הַHebrewH11570NaN1art
333946333947Psalms1365333947wordהַ֭the (art)הַ I1792NaN2הַ֭30380333946024664הַHA-הַ֭HebrewH23298NaN1art
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "362447 362448 Ecclesiastes 9 5 362448 word וְ \n", "414324 414325 2_Chronicles 16 5 414325 word וַ \n", "383061 383062 Ezra 10 14 383062 word וְ \n", "153105 153106 1_Samuel 19 11 153106 word הַ \n", "333946 333947 Psalms 136 5 333947 word הַ֭ \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 bol_dict_abc1 \\\n", "362447 and; also, even (conj); but וְ 1952 \n", "414324 and; also, even (conj); but וְ 1952 \n", "383061 and; also, even (conj); but וְ 1952 \n", "153105 the (art) הַ I 1792 \n", "333946 the (art) הַ I 1792 \n", "\n", " bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "362447 NaN 1 וְ 50273 \n", "414324 NaN 1 וַ 50273 \n", "383061 NaN 1 וְ 50273 \n", "153105 NaN 2 הַ 30380 \n", "333946 NaN 2 הַ֭ 30380 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "362447 362447 0 50238 וְ \n", "414324 414324 0 50238 וַ \n", "383061 383061 0 50238 וְ \n", "153105 153105 0 24664 הַ \n", "333946 333946 0 24664 הַ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 qere_utf81 \\\n", "362447 W:- וְ Hebrew W 3173 NaN \n", "414324 WA- וַ Hebrew W 7505 NaN \n", "383061 W:- וְ Hebrew W 4916 NaN \n", "153105 HA- הַ Hebrew H 11570 NaN \n", "333946 HA- הַ֭ Hebrew H 23298 NaN \n", "\n", " rank_occ1 sp1 \n", "362447 0 conj \n", "414324 0 conj \n", "383061 0 conj \n", "153105 1 art \n", "333946 1 art " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST625_selection_of_random3=BHSallHebrewWords_OTST625.groupby('bol_dict_HebArm1').sample(n=3, replace=True).sort_values(['rank_occ1','bol_dict_abc1'], ascending=True)\n", "BHSallHebrewWords_OTST625_selection_of_random3.head()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_fa_order1bol_g_word_utf81bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1freq_occ1g_lex_utf81g_word_noaccent1g_word_utf81language1lex1number1qere_utf81rank_occ1sp1
362447362448Ecclesiastes95362448wordוְand; also, even (conj); butוְ1952NaN1וְ50273362447050238וְW:-וְHebrewW3173NaN0conj
4143244143252_Chronicles165414325wordוַand; also, even (conj); butוְ1952NaN1וַ50273414324050238וַWA-וַHebrewW7505NaN0conj
383061383062Ezra1014383062wordוְand; also, even (conj); butוְ1952NaN1וְ50273383061050238וְW:-וְHebrewW4916NaN0conj
1531051531061_Samuel1911153106wordהַthe (art)הַ I1792NaN2הַ30380153105024664הַHA-הַHebrewH11570NaN1art
333946333947Psalms1365333947wordהַ֭the (art)הַ I1792NaN2הַ֭30380333946024664הַHA-הַ֭HebrewH23298NaN1art
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "362447 362448 Ecclesiastes 9 5 362448 word וְ \n", "414324 414325 2_Chronicles 16 5 414325 word וַ \n", "383061 383062 Ezra 10 14 383062 word וְ \n", "153105 153106 1_Samuel 19 11 153106 word הַ \n", "333946 333947 Psalms 136 5 333947 word הַ֭ \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 bol_dict_abc1 \\\n", "362447 and; also, even (conj); but וְ 1952 \n", "414324 and; also, even (conj); but וְ 1952 \n", "383061 and; also, even (conj); but וְ 1952 \n", "153105 the (art) הַ I 1792 \n", "333946 the (art) הַ I 1792 \n", "\n", " bol_dict_vc1 bol_fa_order1 bol_g_word_utf81 bol_lexeme_occurrences1 \\\n", "362447 NaN 1 וְ 50273 \n", "414324 NaN 1 וַ 50273 \n", "383061 NaN 1 וְ 50273 \n", "153105 NaN 2 הַ 30380 \n", "333946 NaN 2 הַ֭ 30380 \n", "\n", " bol_monad_num1 bol_qere_presence1 freq_occ1 g_lex_utf81 \\\n", "362447 362447 0 50238 וְ \n", "414324 414324 0 50238 וַ \n", "383061 383061 0 50238 וְ \n", "153105 153105 0 24664 הַ \n", "333946 333946 0 24664 הַ \n", "\n", " g_word_noaccent1 g_word_utf81 language1 lex1 number1 qere_utf81 \\\n", "362447 W:- וְ Hebrew W 3173 NaN \n", "414324 WA- וַ Hebrew W 7505 NaN \n", "383061 W:- וְ Hebrew W 4916 NaN \n", "153105 HA- הַ Hebrew H 11570 NaN \n", "333946 HA- הַ֭ Hebrew H 23298 NaN \n", "\n", " rank_occ1 sp1 \n", "362447 0 conj \n", "414324 0 conj \n", "383061 0 conj \n", "153105 1 art \n", "333946 1 art " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallHebrewWords_OTST625_selection_of_random3.drop_duplicates(subset=\"bol_monad_num1\", keep='first', inplace=True)\n", "BHSallHebrewWords_OTST625_selection_of_random3.head(5)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "BHSallHebrewWords_OTST625_selection_of_random3.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_vocab_OTST_625_Qualifier-Selection_unfiltered_0.3.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reges_I 21:1-17" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 6.58s 58 results\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
npversewordword
11_Kings 21:1אַחַר֙ אַחַר֙
21_Kings 21:1דְּבָרִ֣ים דְּבָרִ֣ים
31_Kings 21:2יְדַבֵּ֣ר יְדַבֵּ֣ר
41_Kings 21:2טֹ֣וב טֹ֣וב
51_Kings 21:2מִמֶּ֑נּוּ מִמֶּ֑נּוּ
61_Kings 21:2טֹ֣וב טֹ֣וב
71_Kings 21:2עֵינֶ֔יךָ עֵינֶ֔יךָ
81_Kings 21:2כֶ֖סֶף כֶ֖סֶף
91_Kings 21:4יָּבֹא֩ יָּבֹא֩
101_Kings 21:4בֵּיתֹ֜ו בֵּיתֹ֜ו
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "RegesVocab='''\n", "verse book=Reges_I chapter=21 verse=1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17\n", " w1:word lex* bol_dict_HebArm* bol_dict_EN* number* freq_occ<700 sp#nmpr rank_occ* bol_fa_order* bol_lexeme_occurrences* bol_dict_abc* language* bol_monad_num* qere_utf8* g_word_utf8* g_lex_utf8* bol_g_word_utf8* bol_qere_presence*\n", " w2:word lex* bol_dict_HebArm* bol_dict_EN* number* freq_occ>100 rank_occ* bol_fa_order* bol_lexeme_occurrences* bol_dict_abc* language* bol_monad_num* qere_utf8* g_word_utf8* g_lex_utf8* bol_g_word_utf8* bol_qere_presence*\n", "\n", "w1 = w2\n", "'''\n", "RegesVocab = BHSa4c.search(RegesVocab)\n", "BHSa4c.table(RegesVocab, start=1, end=10, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "tags": [] }, "outputs": [], "source": [ "BHSa4c.export(RegesVocab, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises', toFile='BHSa4c_BOL_vocab_Reges21.tsv')" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1book1chapter1verse1NODE2TYPE2TEXT2bol_dict_EN2bol_dict_HebArm2bol_dict_abc2bol_fa_order2bol_g_word_utf82bol_lexeme_occurrences2bol_monad_num2bol_qere_presence2freq_occ2g_lex_utf82g_word_utf82language2lex2number2qere_utf82rank_occ2sp2NODE3TYPE3TEXT3bol_dict_EN3bol_dict_HebArm3bol_dict_abc3bol_fa_order3bol_g_word_utf83bol_lexeme_occurrences3bol_monad_num3bol_qere_presence3freq_occ3g_lex_utf83g_word_utf83language3lex3number3qere_utf83rank_occ3
011_Kings2111423723verseוַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם...Reges_I211192989wordאַחַר֙behind, after; back sideאַחַר I30475אַחַר֙7151929880156אַחַראַחַר֙Hebrew>XR/16912NaN281subs192989wordאַחַר֙behind, after; back sideאַחַר I30475אַחַר֙7151929880156אַחַראַחַר֙Hebrew>XR/16912NaN281
121_Kings2111423723verseוַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם...Reges_I211192991wordדְּבָרִ֣יםword; thing, matter; deedדָּבָר I161932דְּבָרִ֣ים14411929900186דְּבָרדְּבָרִ֣יםHebrewDBR/16914NaN228subs192991wordדְּבָרִ֣יםword; thing, matter; deedדָּבָר I161932דְּבָרִ֣ים14411929900186דְּבָרדְּבָרִ֣יםHebrewDBR/16914NaN228
231_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193009wordיְדַבֵּ֣רqal: speak; ni: speak; pi: speak; pu: be spoke...דבר I161639יְדַבֵּ֣ר11381930080240דַבֵּריְדַבֵּ֣רHebrewDBR[16932NaN179verb193009wordיְדַבֵּ֣רqal: speak; ni: speak; pi: speak; pu: be spoke...דבר I161639יְדַבֵּ֣ר11381930080240דַבֵּריְדַבֵּ֣רHebrewDBR[16932NaN179
341_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193035wordטֹ֣ובgood (adj); goodness (n)טֹוב I2797112טֹ֣וב4691930340423טֹובטֹ֣ובHebrewVWB/16958NaN79adjv193035wordטֹ֣ובgood (adj); goodness (n)טֹוב I2797112טֹ֣וב4691930340423טֹובטֹ֣ובHebrewVWB/16958NaN79
451_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193036wordמִמֶּ֑נּוּfrom, out of, part of, because of (prep); than...מִן I43456מִמֶּ֑נּוּ75621930350174מִמֶּןּמִמֶּ֑נּוּHebrewMN16959NaN252prep193036wordמִמֶּ֑נּוּfrom, out of, part of, because of (prep); than...מִן I43456מִמֶּ֑נּוּ75621930350174מִמֶּןּמִמֶּ֑נּוּHebrewMN16959NaN252
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "0 1 1_Kings 21 1 1423723 verse \n", "1 2 1_Kings 21 1 1423723 verse \n", "2 3 1_Kings 21 2 1423724 verse \n", "3 4 1_Kings 21 2 1423724 verse \n", "4 5 1_Kings 21 2 1423724 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם... Reges_I 21 \n", "1 וַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם... Reges_I 21 \n", "2 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "3 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "4 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "\n", " verse1 NODE2 TYPE2 TEXT2 \\\n", "0 1 192989 word אַחַר֙ \n", "1 1 192991 word דְּבָרִ֣ים \n", "2 2 193009 word יְדַבֵּ֣ר \n", "3 2 193035 word טֹ֣וב \n", "4 2 193036 word מִמֶּ֑נּוּ \n", "\n", " bol_dict_EN2 bol_dict_HebArm2 \\\n", "0 behind, after; back side אַחַר I \n", "1 word; thing, matter; deed דָּבָר I \n", "2 qal: speak; ni: speak; pi: speak; pu: be spoke... דבר I \n", "3 good (adj); goodness (n) טֹוב I \n", "4 from, out of, part of, because of (prep); than... מִן I \n", "\n", " bol_dict_abc2 bol_fa_order2 bol_g_word_utf82 bol_lexeme_occurrences2 \\\n", "0 304 75 אַחַר֙ 715 \n", "1 1619 32 דְּבָרִ֣ים 1441 \n", "2 1616 39 יְדַבֵּ֣ר 1138 \n", "3 2797 112 טֹ֣וב 469 \n", "4 4345 6 מִמֶּ֑נּוּ 7562 \n", "\n", " bol_monad_num2 bol_qere_presence2 freq_occ2 g_lex_utf82 g_word_utf82 \\\n", "0 192988 0 156 אַחַר אַחַר֙ \n", "1 192990 0 186 דְּבָר דְּבָרִ֣ים \n", "2 193008 0 240 דַבֵּר יְדַבֵּ֣ר \n", "3 193034 0 423 טֹוב טֹ֣וב \n", "4 193035 0 174 מִמֶּןּ מִמֶּ֑נּוּ \n", "\n", " language2 lex2 number2 qere_utf82 rank_occ2 sp2 NODE3 TYPE3 \\\n", "0 Hebrew >XR/ 16912 NaN 281 subs 192989 word \n", "1 Hebrew DBR/ 16914 NaN 228 subs 192991 word \n", "2 Hebrew DBR[ 16932 NaN 179 verb 193009 word \n", "3 Hebrew VWB/ 16958 NaN 79 adjv 193035 word \n", "4 Hebrew MN 16959 NaN 252 prep 193036 word \n", "\n", " TEXT3 bol_dict_EN3 \\\n", "0 אַחַר֙ behind, after; back side \n", "1 דְּבָרִ֣ים word; thing, matter; deed \n", "2 יְדַבֵּ֣ר qal: speak; ni: speak; pi: speak; pu: be spoke... \n", "3 טֹ֣וב good (adj); goodness (n) \n", "4 מִמֶּ֑נּוּ from, out of, part of, because of (prep); than... \n", "\n", " bol_dict_HebArm3 bol_dict_abc3 bol_fa_order3 bol_g_word_utf83 \\\n", "0 אַחַר I 304 75 אַחַר֙ \n", "1 דָּבָר I 1619 32 דְּבָרִ֣ים \n", "2 דבר I 1616 39 יְדַבֵּ֣ר \n", "3 טֹוב I 2797 112 טֹ֣וב \n", "4 מִן I 4345 6 מִמֶּ֑נּוּ \n", "\n", " bol_lexeme_occurrences3 bol_monad_num3 bol_qere_presence3 freq_occ3 \\\n", "0 715 192988 0 156 \n", "1 1441 192990 0 186 \n", "2 1138 193008 0 240 \n", "3 469 193034 0 423 \n", "4 7562 193035 0 174 \n", "\n", " g_lex_utf83 g_word_utf83 language3 lex3 number3 qere_utf83 rank_occ3 \n", "0 אַחַר אַחַר֙ Hebrew >XR/ 16912 NaN 281 \n", "1 דְּבָר דְּבָרִ֣ים Hebrew DBR/ 16914 NaN 228 \n", "2 דַבֵּר יְדַבֵּ֣ר Hebrew DBR[ 16932 NaN 179 \n", "3 טֹוב טֹ֣וב Hebrew VWB/ 16958 NaN 79 \n", "4 מִמֶּןּ מִמֶּ֑נּוּ Hebrew MN 16959 NaN 252 " ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "Reges21Vocab=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_vocab_Reges21.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "Reges21Vocab.head()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS2S3NODE1chapter1verse1NODE2bol_dict_abc2bol_fa_order2bol_lexeme_occurrences2bol_monad_num2bol_qere_presence2freq_occ2number2qere_utf82rank_occ2NODE3bol_dict_abc3bol_fa_order3bol_lexeme_occurrences3bol_monad_num3bol_qere_presence3freq_occ3number3qere_utf83rank_occ3
count58.00000058.058.0000005.800000e+0158.058.00000058.00000058.00000058.00000058.00000058.00000058.058.00000058.0000000.058.00000058.00000058.00000058.00000058.00000058.00000058.058.00000058.0000000.058.000000
mean29.50000021.08.5000001.423730e+0621.08.500000193188.3103453273.79310370.9137931852.465517193187.3103450.0255.06896617111.310345NaN202.775862193188.3103453273.79310370.9137931852.465517193187.3103450.0255.06896617111.310345NaN202.775862
std16.8868790.04.7581884.758188e+000.04.758188114.6581812525.936969110.7572481822.351250114.6581810.0123.009180114.658181NaN103.593342114.6581812525.936969110.7572481822.351250114.6581810.0123.009180114.658181NaN103.593342
min1.00000021.01.0000001.423723e+0621.01.000000192989.000000170.0000006.00000044.000000192988.0000000.0102.00000016912.000000NaN53.000000192989.000000170.0000006.00000044.000000192988.0000000.0102.00000016912.000000NaN53.000000
25%15.25000021.04.2500001.423726e+0621.04.250000193097.750000430.25000025.000000650.500000193096.7500000.0158.00000017020.750000NaN105.000000193097.750000430.25000025.000000650.500000193096.7500000.0158.00000017020.750000NaN105.000000
50%29.50000021.07.0000001.423729e+0621.07.000000193159.5000003577.00000040.5000001086.000000193158.5000000.0245.50000017082.500000NaN176.000000193159.5000003577.00000040.5000001086.000000193158.5000000.0245.50000017082.500000NaN176.000000
75%43.75000021.013.0000001.423735e+0621.013.000000193282.0000005268.00000079.5000002186.000000193281.0000000.0351.00000017205.000000NaN278.000000193282.0000005268.00000079.5000002186.000000193281.0000000.0351.00000017205.000000NaN278.000000
max58.00000021.016.0000001.423738e+0621.016.000000193370.0000007905.000000819.0000007562.000000193369.0000000.0634.00000017293.000000NaN416.000000193370.0000007905.000000819.0000007562.000000193369.0000000.0634.00000017293.000000NaN416.000000
\n", "
" ], "text/plain": [ " R S2 S3 NODE1 chapter1 verse1 \\\n", "count 58.000000 58.0 58.000000 5.800000e+01 58.0 58.000000 \n", "mean 29.500000 21.0 8.500000 1.423730e+06 21.0 8.500000 \n", "std 16.886879 0.0 4.758188 4.758188e+00 0.0 4.758188 \n", "min 1.000000 21.0 1.000000 1.423723e+06 21.0 1.000000 \n", "25% 15.250000 21.0 4.250000 1.423726e+06 21.0 4.250000 \n", "50% 29.500000 21.0 7.000000 1.423729e+06 21.0 7.000000 \n", "75% 43.750000 21.0 13.000000 1.423735e+06 21.0 13.000000 \n", "max 58.000000 21.0 16.000000 1.423738e+06 21.0 16.000000 \n", "\n", " NODE2 bol_dict_abc2 bol_fa_order2 bol_lexeme_occurrences2 \\\n", "count 58.000000 58.000000 58.000000 58.000000 \n", "mean 193188.310345 3273.793103 70.913793 1852.465517 \n", "std 114.658181 2525.936969 110.757248 1822.351250 \n", "min 192989.000000 170.000000 6.000000 44.000000 \n", "25% 193097.750000 430.250000 25.000000 650.500000 \n", "50% 193159.500000 3577.000000 40.500000 1086.000000 \n", "75% 193282.000000 5268.000000 79.500000 2186.000000 \n", "max 193370.000000 7905.000000 819.000000 7562.000000 \n", "\n", " bol_monad_num2 bol_qere_presence2 freq_occ2 number2 \\\n", "count 58.000000 58.0 58.000000 58.000000 \n", "mean 193187.310345 0.0 255.068966 17111.310345 \n", "std 114.658181 0.0 123.009180 114.658181 \n", "min 192988.000000 0.0 102.000000 16912.000000 \n", "25% 193096.750000 0.0 158.000000 17020.750000 \n", "50% 193158.500000 0.0 245.500000 17082.500000 \n", "75% 193281.000000 0.0 351.000000 17205.000000 \n", "max 193369.000000 0.0 634.000000 17293.000000 \n", "\n", " qere_utf82 rank_occ2 NODE3 bol_dict_abc3 bol_fa_order3 \\\n", "count 0.0 58.000000 58.000000 58.000000 58.000000 \n", "mean NaN 202.775862 193188.310345 3273.793103 70.913793 \n", "std NaN 103.593342 114.658181 2525.936969 110.757248 \n", "min NaN 53.000000 192989.000000 170.000000 6.000000 \n", "25% NaN 105.000000 193097.750000 430.250000 25.000000 \n", "50% NaN 176.000000 193159.500000 3577.000000 40.500000 \n", "75% NaN 278.000000 193282.000000 5268.000000 79.500000 \n", "max NaN 416.000000 193370.000000 7905.000000 819.000000 \n", "\n", " bol_lexeme_occurrences3 bol_monad_num3 bol_qere_presence3 \\\n", "count 58.000000 58.000000 58.0 \n", "mean 1852.465517 193187.310345 0.0 \n", "std 1822.351250 114.658181 0.0 \n", "min 44.000000 192988.000000 0.0 \n", "25% 650.500000 193096.750000 0.0 \n", "50% 1086.000000 193158.500000 0.0 \n", "75% 2186.000000 193281.000000 0.0 \n", "max 7562.000000 193369.000000 0.0 \n", "\n", " freq_occ3 number3 qere_utf83 rank_occ3 \n", "count 58.000000 58.000000 0.0 58.000000 \n", "mean 255.068966 17111.310345 NaN 202.775862 \n", "std 123.009180 114.658181 NaN 103.593342 \n", "min 102.000000 16912.000000 NaN 53.000000 \n", "25% 158.000000 17020.750000 NaN 105.000000 \n", "50% 245.500000 17082.500000 NaN 176.000000 \n", "75% 351.000000 17205.000000 NaN 278.000000 \n", "max 634.000000 17293.000000 NaN 416.000000 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Reges21Vocab.describe()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1book1chapter1verse1NODE2TYPE2TEXT2bol_dict_EN2bol_dict_HebArm2bol_dict_abc2bol_fa_order2bol_g_word_utf82bol_lexeme_occurrences2bol_monad_num2bol_qere_presence2freq_occ2g_lex_utf82g_word_utf82language2lex2number2qere_utf82rank_occ2sp2NODE3TYPE3TEXT3bol_dict_EN3bol_dict_HebArm3bol_dict_abc3bol_fa_order3bol_g_word_utf83bol_lexeme_occurrences3bol_monad_num3bol_qere_presence3freq_occ3g_lex_utf83g_word_utf83language3lex3number3qere_utf83rank_occ3
011_Kings2111423723verseוַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם...Reges_I211192989wordאַחַר֙behind, after; back sideאַחַר I30475אַחַר֙7151929880156אַחַראַחַר֙Hebrew>XR/16912NaN281subs192989wordאַחַר֙behind, after; back sideאַחַר I30475אַחַר֙7151929880156אַחַראַחַר֙Hebrew>XR/16912NaN281
121_Kings2111423723verseוַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם...Reges_I211192991wordדְּבָרִ֣יםword; thing, matter; deedדָּבָר I161932דְּבָרִ֣ים14411929900186דְּבָרדְּבָרִ֣יםHebrewDBR/16914NaN228subs192991wordדְּבָרִ֣יםword; thing, matter; deedדָּבָר I161932דְּבָרִ֣ים14411929900186דְּבָרדְּבָרִ֣יםHebrewDBR/16914NaN228
231_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193009wordיְדַבֵּ֣רqal: speak; ni: speak; pi: speak; pu: be spoke...דבר I161639יְדַבֵּ֣ר11381930080240דַבֵּריְדַבֵּ֣רHebrewDBR[16932NaN179verb193009wordיְדַבֵּ֣רqal: speak; ni: speak; pi: speak; pu: be spoke...דבר I161639יְדַבֵּ֣ר11381930080240דַבֵּריְדַבֵּ֣רHebrewDBR[16932NaN179
341_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193035wordטֹ֣ובgood (adj); goodness (n)טֹוב I2797112טֹ֣וב4691930340423טֹובטֹ֣ובHebrewVWB/16958NaN79adjv193035wordטֹ֣ובgood (adj); goodness (n)טֹוב I2797112טֹ֣וב4691930340423טֹובטֹ֣ובHebrewVWB/16958NaN79
451_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193036wordמִמֶּ֑נּוּfrom, out of, part of, because of (prep); than...מִן I43456מִמֶּ֑נּוּ75621930350174מִמֶּןּמִמֶּ֑נּוּHebrewMN16959NaN252prep193036wordמִמֶּ֑נּוּfrom, out of, part of, because of (prep); than...מִן I43456מִמֶּ֑נּוּ75621930350174מִמֶּןּמִמֶּ֑נּוּHebrewMN16959NaN252
561_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193038wordטֹ֣ובqal: be good, be pleasant; hi: act right;טוב2800819טֹ֣וב441930370423טֹובטֹ֣ובHebrewVWB[16961NaN79verb193038wordטֹ֣ובqal: be good, be pleasant; hi: act right;טוב2800819טֹ֣וב441930370423טֹובטֹ֣ובHebrewVWB[16961NaN79
671_Kings2121423724verseוַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ...Reges_I212193040wordעֵינֶ֔יךָeye; fountainעַיִן I574252עֵינֶ֔יךָ8871930390148עֵיןעֵינֶ֔יךָHebrew<JN/16963NaN288subs193040wordעֵינֶ֔יךָeye; fountainעַיִן I574252עֵינֶ֔יךָ8871930390148עֵיןעֵינֶ֔יךָHebrew<JN/16963NaN288
9101_Kings2141423726verseוַיָּבֹא֩ אַחְאָ֨ב אֶל־בֵּיתֹ֜ו סַ֣ר וְזָעֵ֗ף ...Reges_I214193065wordבֵּיתֹ֜וhouse; familyבַּיִת95727בֵּיתֹ֜ו20631930640169בֵּיתבֵּיתֹ֜וHebrewBJT/16988NaN262subs193065wordבֵּיתֹ֜וhouse; familyבַּיִת95727בֵּיתֹ֜ו20631930640169בֵּיתבֵּיתֹ֜וHebrewBJT/16988NaN262
12131_Kings2141423726verseוַיָּבֹא֩ אַחְאָ֨ב אֶל־בֵּיתֹ֜ו סַ֣ר וְזָעֵ֗ף ...Reges_I214193093wordפָּנָ֖יוface; surface; frontפָּנֶה I631726פָּנָ֖יו21271930920251פָּןפָּנָ֖יוHebrewPNH/17016NaN173subs193093wordפָּנָ֖יוface; surface; frontפָּנֶה I631726פָּנָ֖יו21271930920251פָּןפָּנָ֖יוHebrewPNH/17016NaN173
13141_Kings2141423726verseוַיָּבֹא֩ אַחְאָ֨ב אֶל־בֵּיתֹ֜ו סַ֣ר וְזָעֵ֗ף ...Reges_I214193096wordאָ֥כַלqal: eat, devour; qal pass: eat; ni: be eaten;...אכל38361אָ֥כַל8101930950164אָכַלאָ֥כַלHebrew>KL[17019NaN269verb193096wordאָ֥כַלqal: eat, devour; qal pass: eat; ni: be eaten;...אכל38361אָ֥כַל8101930950164אָכַלאָ֥כַלHebrew>KL[17019NaN269
16171_Kings2151423727verseוַתָּבֹ֥א אֵלָ֖יו אִיזֶ֣בֶל אִשְׁתֹּ֑ו וַתְּדַ...Reges_I215193105wordאֵלָ֗יוtoward (prep), unto; towardsאֶל I3929אֵלָ֗יו55171931040430אֵלָיאֵלָ֗יוHebrew>L17028NaN77prep193105wordאֵלָ֗יוtoward (prep), unto; towardsאֶל I3929אֵלָ֗יו55171931040430אֵלָיאֵלָ֗יוHebrew>L17028NaN77
17181_Kings2151423727verseוַתָּבֹ֥א אֵלָ֖יו אִיזֶ֣בֶל אִשְׁתֹּ֑ו וַתְּדַ...Reges_I215193106wordמַה־what (interr), how (interr)מָה397091מַה5731931050567מַהמַהHebrewMH17029NaN63prin193106wordמַה־what (interr), how (interr)מָה397091מַה5731931050567מַהמַהHebrewMH17029NaN63
22231_Kings2161423728verseוַיְדַבֵּ֣ר אֵלֶ֗יהָ כִּֽי־אֲ֠דַבֵּר אֶל־נָבֹ֨...Reges_I216193132wordאֹ֚וor, or evenאֹו170155אֹ֚ו3201931310321אֹואֹ֚וHebrew>W17055NaN114conj193132wordאֹ֚וor, or evenאֹו170155אֹ֚ו3201931310321אֹואֹ֚וHebrew>W17055NaN114
24251_Kings2171423729verseוַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕...Reges_I217193148wordתֹּ֤אמֶרqal: say, think; ni: be said, be called; hi: d...אמר I54512תֹּ֤אמֶר53071931470259אמֶרתֹּ֤אמֶרHebrew>MR[17071NaN157verb193148wordתֹּ֤אמֶרqal: say, think; ni: be said, be called; hi: d...אמר I54512תֹּ֤אמֶר53071931470259אמֶרתֹּ֤אמֶרHebrew>MR[17071NaN157
26271_Kings2171423729verseוַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕...Reges_I217193153wordעַתָּ֛הnowעַתָּה6136119עַתָּ֛ה4331931520435עַתָּהעַתָּ֛הHebrew<TH17076NaN75advb193153wordעַתָּ֛הnowעַתָּה6136119עַתָּ֛ה4331931520435עַתָּהעַתָּ֛הHebrew<TH17076NaN75
27281_Kings2171423729verseוַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕...Reges_I217193154wordתַּעֲשֶׂ֥הqal: do, make; ni: be made, done; pi: press, s...עשׂה611818תַּעֲשֶׂ֥ה26291931530141עֲשֶׂהתַּעֲשֶׂ֥הHebrew<FH[17077NaN303verb193154wordתַּעֲשֶׂ֥הqal: do, make; ni: be made, done; pi: press, s...עשׂה611818תַּעֲשֶׂ֥ה26291931530141עֲשֶׂהתַּעֲשֶׂ֥הHebrew<FH[17077NaN303
29301_Kings2171423729verseוַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕...Reges_I217193160wordלֶ֨חֶם֙bread, foodלֶחֶם I3774164לֶ֨חֶם֙2981931590254לֶחֶםלֶ֨חֶם֙HebrewLXM/17083NaN168subs193160wordלֶ֨חֶם֙bread, foodלֶחֶם I3774164לֶ֨חֶם֙2981931590254לֶחֶםלֶ֨חֶם֙HebrewLXM/17083NaN168
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "0 1 1_Kings 21 1 1423723 verse \n", "1 2 1_Kings 21 1 1423723 verse \n", "2 3 1_Kings 21 2 1423724 verse \n", "3 4 1_Kings 21 2 1423724 verse \n", "4 5 1_Kings 21 2 1423724 verse \n", "5 6 1_Kings 21 2 1423724 verse \n", "6 7 1_Kings 21 2 1423724 verse \n", "9 10 1_Kings 21 4 1423726 verse \n", "12 13 1_Kings 21 4 1423726 verse \n", "13 14 1_Kings 21 4 1423726 verse \n", "16 17 1_Kings 21 5 1423727 verse \n", "17 18 1_Kings 21 5 1423727 verse \n", "22 23 1_Kings 21 6 1423728 verse \n", "24 25 1_Kings 21 7 1423729 verse \n", "26 27 1_Kings 21 7 1423729 verse \n", "27 28 1_Kings 21 7 1423729 verse \n", "29 30 1_Kings 21 7 1423729 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם... Reges_I 21 \n", "1 וַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה כֶּ֧רֶם... Reges_I 21 \n", "2 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "3 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "4 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "5 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "6 וַיְדַבֵּ֣ר אַחְאָ֣ב אֶל־נָבֹ֣ות׀ לֵאמֹר֩׀ תְּ... Reges_I 21 \n", "9 וַיָּבֹא֩ אַחְאָ֨ב אֶל־בֵּיתֹ֜ו סַ֣ר וְזָעֵ֗ף ... Reges_I 21 \n", "12 וַיָּבֹא֩ אַחְאָ֨ב אֶל־בֵּיתֹ֜ו סַ֣ר וְזָעֵ֗ף ... Reges_I 21 \n", "13 וַיָּבֹא֩ אַחְאָ֨ב אֶל־בֵּיתֹ֜ו סַ֣ר וְזָעֵ֗ף ... Reges_I 21 \n", "16 וַתָּבֹ֥א אֵלָ֖יו אִיזֶ֣בֶל אִשְׁתֹּ֑ו וַתְּדַ... Reges_I 21 \n", "17 וַתָּבֹ֥א אֵלָ֖יו אִיזֶ֣בֶל אִשְׁתֹּ֑ו וַתְּדַ... Reges_I 21 \n", "22 וַיְדַבֵּ֣ר אֵלֶ֗יהָ כִּֽי־אֲ֠דַבֵּר אֶל־נָבֹ֨... Reges_I 21 \n", "24 וַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕... Reges_I 21 \n", "26 וַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕... Reges_I 21 \n", "27 וַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕... Reges_I 21 \n", "29 וַתֹּ֤אמֶר אֵלָיו֙ אִיזֶ֣בֶל אִשְׁתֹּ֔ו אַתָּ֕... Reges_I 21 \n", "\n", " verse1 NODE2 TYPE2 TEXT2 \\\n", "0 1 192989 word אַחַר֙ \n", "1 1 192991 word דְּבָרִ֣ים \n", "2 2 193009 word יְדַבֵּ֣ר \n", "3 2 193035 word טֹ֣וב \n", "4 2 193036 word מִמֶּ֑נּוּ \n", "5 2 193038 word טֹ֣וב \n", "6 2 193040 word עֵינֶ֔יךָ \n", "9 4 193065 word בֵּיתֹ֜ו \n", "12 4 193093 word פָּנָ֖יו \n", "13 4 193096 word אָ֥כַל \n", "16 5 193105 word אֵלָ֗יו \n", "17 5 193106 word מַה־ \n", "22 6 193132 word אֹ֚ו \n", "24 7 193148 word תֹּ֤אמֶר \n", "26 7 193153 word עַתָּ֛ה \n", "27 7 193154 word תַּעֲשֶׂ֥ה \n", "29 7 193160 word לֶ֨חֶם֙ \n", "\n", " bol_dict_EN2 bol_dict_HebArm2 \\\n", "0 behind, after; back side אַחַר I \n", "1 word; thing, matter; deed דָּבָר I \n", "2 qal: speak; ni: speak; pi: speak; pu: be spoke... דבר I \n", "3 good (adj); goodness (n) טֹוב I \n", "4 from, out of, part of, because of (prep); than... מִן I \n", "5 qal: be good, be pleasant; hi: act right; טוב \n", "6 eye; fountain עַיִן I \n", "9 house; family בַּיִת \n", "12 face; surface; front פָּנֶה I \n", "13 qal: eat, devour; qal pass: eat; ni: be eaten;... אכל \n", "16 toward (prep), unto; towards אֶל I \n", "17 what (interr), how (interr) מָה \n", "22 or, or even אֹו \n", "24 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "26 now עַתָּה \n", "27 qal: do, make; ni: be made, done; pi: press, s... עשׂה \n", "29 bread, food לֶחֶם I \n", "\n", " bol_dict_abc2 bol_fa_order2 bol_g_word_utf82 bol_lexeme_occurrences2 \\\n", "0 304 75 אַחַר֙ 715 \n", "1 1619 32 דְּבָרִ֣ים 1441 \n", "2 1616 39 יְדַבֵּ֣ר 1138 \n", "3 2797 112 טֹ֣וב 469 \n", "4 4345 6 מִמֶּ֑נּוּ 7562 \n", "5 2800 819 טֹ֣וב 44 \n", "6 5742 52 עֵינֶ֔יךָ 887 \n", "9 957 27 בֵּיתֹ֜ו 2063 \n", "12 6317 26 פָּנָ֖יו 2127 \n", "13 383 61 אָ֥כַל 810 \n", "16 392 9 אֵלָ֗יו 5517 \n", "17 3970 91 מַה 573 \n", "22 170 155 אֹ֚ו 320 \n", "24 545 12 תֹּ֤אמֶר 5307 \n", "26 6136 119 עַתָּ֛ה 433 \n", "27 6118 18 תַּעֲשֶׂ֥ה 2629 \n", "29 3774 164 לֶ֨חֶם֙ 298 \n", "\n", " bol_monad_num2 bol_qere_presence2 freq_occ2 g_lex_utf82 g_word_utf82 \\\n", "0 192988 0 156 אַחַר אַחַר֙ \n", "1 192990 0 186 דְּבָר דְּבָרִ֣ים \n", "2 193008 0 240 דַבֵּר יְדַבֵּ֣ר \n", "3 193034 0 423 טֹוב טֹ֣וב \n", "4 193035 0 174 מִמֶּןּ מִמֶּ֑נּוּ \n", "5 193037 0 423 טֹוב טֹ֣וב \n", "6 193039 0 148 עֵין עֵינֶ֔יךָ \n", "9 193064 0 169 בֵּית בֵּיתֹ֜ו \n", "12 193092 0 251 פָּן פָּנָ֖יו \n", "13 193095 0 164 אָכַל אָ֥כַל \n", "16 193104 0 430 אֵלָי אֵלָ֗יו \n", "17 193105 0 567 מַה מַה \n", "22 193131 0 321 אֹו אֹ֚ו \n", "24 193147 0 259 אמֶר תֹּ֤אמֶר \n", "26 193152 0 435 עַתָּה עַתָּ֛ה \n", "27 193153 0 141 עֲשֶׂה תַּעֲשֶׂ֥ה \n", "29 193159 0 254 לֶחֶם לֶ֨חֶם֙ \n", "\n", " language2 lex2 number2 qere_utf82 rank_occ2 sp2 NODE3 TYPE3 \\\n", "0 Hebrew >XR/ 16912 NaN 281 subs 192989 word \n", "1 Hebrew DBR/ 16914 NaN 228 subs 192991 word \n", "2 Hebrew DBR[ 16932 NaN 179 verb 193009 word \n", "3 Hebrew VWB/ 16958 NaN 79 adjv 193035 word \n", "4 Hebrew MN 16959 NaN 252 prep 193036 word \n", "5 Hebrew VWB[ 16961 NaN 79 verb 193038 word \n", "6 Hebrew KL[ 17019 NaN 269 verb 193096 word \n", "16 Hebrew >L 17028 NaN 77 prep 193105 word \n", "17 Hebrew MH 17029 NaN 63 prin 193106 word \n", "22 Hebrew >W 17055 NaN 114 conj 193132 word \n", "24 Hebrew >MR[ 17071 NaN 157 verb 193148 word \n", "26 Hebrew XR/ 16912 NaN 281 \n", "1 דְּבָר דְּבָרִ֣ים Hebrew DBR/ 16914 NaN 228 \n", "2 דַבֵּר יְדַבֵּ֣ר Hebrew DBR[ 16932 NaN 179 \n", "3 טֹוב טֹ֣וב Hebrew VWB/ 16958 NaN 79 \n", "4 מִמֶּןּ מִמֶּ֑נּוּ Hebrew MN 16959 NaN 252 \n", "5 טֹוב טֹ֣וב Hebrew VWB[ 16961 NaN 79 \n", "6 עֵין עֵינֶ֔יךָ Hebrew KL[ 17019 NaN 269 \n", "16 אֵלָי אֵלָ֗יו Hebrew >L 17028 NaN 77 \n", "17 מַה מַה Hebrew MH 17029 NaN 63 \n", "22 אֹו אֹ֚ו Hebrew >W 17055 NaN 114 \n", "24 אמֶר תֹּ֤אמֶר Hebrew >MR[ 17071 NaN 157 \n", "26 עַתָּה עַתָּ֛ה Hebrew \n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS2S3NODE1chapter1verse1NODE2bol_dict_abc2bol_fa_order2bol_lexeme_occurrences2bol_monad_num2bol_qere_presence2freq_occ2number2qere_utf82rank_occ2NODE3bol_dict_abc3bol_fa_order3bol_lexeme_occurrences3bol_monad_num3bol_qere_presence3freq_occ3number3qere_utf83rank_occ3
count29.00000029.029.0000002.900000e+0129.029.00000029.00000029.00000029.00000029.00000029.00000029.029.00000029.0000000.029.00000029.00000029.00000029.00000029.00000029.00000029.029.00000029.0000000.029.000000
mean27.41379321.07.9655171.423730e+0621.07.965517193174.3448283560.31034590.7241381582.862069193173.3448280.0276.58620717097.344828NaN183.000000193174.3448283560.31034590.7241381582.862069193173.3448280.0276.58620717097.344828NaN183.000000
std19.0197590.05.2812525.281252e+000.05.281252128.0539162542.044496148.8409741757.232640128.0539160.0133.926824128.053916NaN90.427161128.0539162542.044496148.8409741757.232640128.0539160.0133.926824128.053916NaN90.427161
min1.00000021.01.0000001.423723e+0621.01.000000192989.000000170.0000006.00000044.000000192988.0000000.0124.00000016912.000000NaN53.000000192989.000000170.0000006.00000044.000000192988.0000000.0124.00000016912.000000NaN53.000000
25%10.00000021.04.0000001.423726e+0621.04.000000193065.000000957.00000027.000000573.000000193064.0000000.0169.00000016988.000000NaN96.000000193065.000000957.00000027.000000573.000000193064.0000000.0169.00000016988.000000NaN96.000000
50%27.00000021.07.0000001.423729e+0621.07.000000193153.0000003577.00000052.000000887.000000193152.0000000.0254.00000017076.000000NaN168.000000193153.0000003577.00000052.000000887.000000193152.0000000.0254.00000017076.000000NaN168.000000
75%44.00000021.013.0000001.423735e+0621.013.000000193283.0000005769.00000091.0000002063.000000193282.0000000.0371.00000017206.000000NaN262.000000193283.0000005769.00000091.0000002063.000000193282.0000000.0371.00000017206.000000NaN262.000000
max58.00000021.016.0000001.423738e+0621.016.000000193370.0000007905.000000819.0000007562.000000193369.0000000.0634.00000017293.000000NaN348.000000193370.0000007905.000000819.0000007562.000000193369.0000000.0634.00000017293.000000NaN348.000000
\n", "" ], "text/plain": [ " R S2 S3 NODE1 chapter1 verse1 \\\n", "count 29.000000 29.0 29.000000 2.900000e+01 29.0 29.000000 \n", "mean 27.413793 21.0 7.965517 1.423730e+06 21.0 7.965517 \n", "std 19.019759 0.0 5.281252 5.281252e+00 0.0 5.281252 \n", "min 1.000000 21.0 1.000000 1.423723e+06 21.0 1.000000 \n", "25% 10.000000 21.0 4.000000 1.423726e+06 21.0 4.000000 \n", "50% 27.000000 21.0 7.000000 1.423729e+06 21.0 7.000000 \n", "75% 44.000000 21.0 13.000000 1.423735e+06 21.0 13.000000 \n", "max 58.000000 21.0 16.000000 1.423738e+06 21.0 16.000000 \n", "\n", " NODE2 bol_dict_abc2 bol_fa_order2 bol_lexeme_occurrences2 \\\n", "count 29.000000 29.000000 29.000000 29.000000 \n", "mean 193174.344828 3560.310345 90.724138 1582.862069 \n", "std 128.053916 2542.044496 148.840974 1757.232640 \n", "min 192989.000000 170.000000 6.000000 44.000000 \n", "25% 193065.000000 957.000000 27.000000 573.000000 \n", "50% 193153.000000 3577.000000 52.000000 887.000000 \n", "75% 193283.000000 5769.000000 91.000000 2063.000000 \n", "max 193370.000000 7905.000000 819.000000 7562.000000 \n", "\n", " bol_monad_num2 bol_qere_presence2 freq_occ2 number2 \\\n", "count 29.000000 29.0 29.000000 29.000000 \n", "mean 193173.344828 0.0 276.586207 17097.344828 \n", "std 128.053916 0.0 133.926824 128.053916 \n", "min 192988.000000 0.0 124.000000 16912.000000 \n", "25% 193064.000000 0.0 169.000000 16988.000000 \n", "50% 193152.000000 0.0 254.000000 17076.000000 \n", "75% 193282.000000 0.0 371.000000 17206.000000 \n", "max 193369.000000 0.0 634.000000 17293.000000 \n", "\n", " qere_utf82 rank_occ2 NODE3 bol_dict_abc3 bol_fa_order3 \\\n", "count 0.0 29.000000 29.000000 29.000000 29.000000 \n", "mean NaN 183.000000 193174.344828 3560.310345 90.724138 \n", "std NaN 90.427161 128.053916 2542.044496 148.840974 \n", "min NaN 53.000000 192989.000000 170.000000 6.000000 \n", "25% NaN 96.000000 193065.000000 957.000000 27.000000 \n", "50% NaN 168.000000 193153.000000 3577.000000 52.000000 \n", "75% NaN 262.000000 193283.000000 5769.000000 91.000000 \n", "max NaN 348.000000 193370.000000 7905.000000 819.000000 \n", "\n", " bol_lexeme_occurrences3 bol_monad_num3 bol_qere_presence3 \\\n", "count 29.000000 29.000000 29.0 \n", "mean 1582.862069 193173.344828 0.0 \n", "std 1757.232640 128.053916 0.0 \n", "min 44.000000 192988.000000 0.0 \n", "25% 573.000000 193064.000000 0.0 \n", "50% 887.000000 193152.000000 0.0 \n", "75% 2063.000000 193282.000000 0.0 \n", "max 7562.000000 193369.000000 0.0 \n", "\n", " freq_occ3 number3 qere_utf83 rank_occ3 \n", "count 29.000000 29.000000 0.0 29.000000 \n", "mean 276.586207 17097.344828 NaN 183.000000 \n", "std 133.926824 128.053916 NaN 90.427161 \n", "min 124.000000 16912.000000 NaN 53.000000 \n", "25% 169.000000 16988.000000 NaN 96.000000 \n", "50% 254.000000 17076.000000 NaN 168.000000 \n", "75% 371.000000 17206.000000 NaN 262.000000 \n", "max 634.000000 17293.000000 NaN 348.000000 " ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Reges21Vocab.describe()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "Reges21Vocab.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/OTST551-2_exams_og/OTST552_week12_midterm-sample_Reges21_vocab_selection.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Morphology" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Analysing first/old version of Selection" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_monad_num1bol_qere_presence1bol_vt1freq_lex1freq_occ1g_word_noaccent1language1lex1ps1nu1gn1number1pdp1prs_ps1prs_nu1prs_gn1rank_occ1sp1st1vs1vt1course approvedregular verbs onlyno suffixtranspositionparagogic nunPielPualHitpael without DFshould be excludedambiguity not solvedketiv-qerequiz dayteaching days/weeksselectlearned vocab
06410Exodus141236462wordנַֽעַבְדָ֣ה36462qal: serve; ni: be cultivated; pu: it is worke...עבד5511i-guttural364610coho2883NA<AB:D@HHebrew<BD[p1plunknown7699verbunknownunknownunknown7211verbNaNqalimpfNaNNaNNaNNaNNaNNaNxNaNNaNNaNNaNNaN200.0
136183Isaiah214218782wordבִּֽעֲתָ֑תְנִי218782ni: be terrified; pi: terrify;בעת1137ii-guttural2187810perf161B.I<:AT@T:NIJHebrewB<T[p3sgf6713verbp1sgunknown12851verbNaNpielperfNaNNaNNaNNaNNaNNaNxxNaNNaNNaNNaNNaN
260217Job1811340535wordבִּֽעֲתֻ֣הוּ340535ni: be terrified; pi: terrify;בעת1137ii-guttural3405340perf161B.I<:ATUHW.HebrewB<T[p3plunknown4515verbp3sgm12851verbNaNpielperfNaNNaNNaNNaNNaNNaNxxNaNNaNNaNNaNNaN
3326782_Kings617198501wordמָלֵ֨א198501qal: be full, fill (with), be filled (with); n...מלא4250iii-aleph1985000ptca29288M@L;>HebrewML>[unknownsgm3739verbunknownunknownunknown472verbaqalptcaNaNNaNNaNNaNNaNNaNxxNaNNaNNaNNaN200.0
4328632_Kings715199366wordמְלֵאָ֤ה199366qal: be full, fill (with), be filled (with); n...מלא4250iii-aleph1993650ptca29252M:L;>@HHebrewML>[unknownsgf4604verbunknownunknownunknown766verbaqalptcaNaNNaNNaNNaNNaNNaNxxNaNNaNNaNNaN200.0
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 6410 Exodus 14 12 36462 word נַֽעַבְדָ֣ה \n", "1 36183 Isaiah 21 4 218782 word בִּֽעֲתָ֑תְנִי \n", "2 60217 Job 18 11 340535 word בִּֽעֲתֻ֣הוּ \n", "3 32678 2_Kings 6 17 198501 word מָלֵ֨א \n", "4 32863 2_Kings 7 15 199366 word מְלֵאָ֤ה \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "0 36462 qal: serve; ni: be cultivated; pu: it is worke... \n", "1 218782 ni: be terrified; pi: terrify; \n", "2 340535 ni: be terrified; pi: terrify; \n", "3 198501 qal: be full, fill (with), be filled (with); n... \n", "4 199366 qal: be full, fill (with), be filled (with); n... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 bol_monad_num1 \\\n", "0 עבד 5511 i-guttural 36461 \n", "1 בעת 1137 ii-guttural 218781 \n", "2 בעת 1137 ii-guttural 340534 \n", "3 מלא 4250 iii-aleph 198500 \n", "4 מלא 4250 iii-aleph 199365 \n", "\n", " bol_qere_presence1 bol_vt1 freq_lex1 freq_occ1 g_word_noaccent1 \\\n", "0 0 coho 288 3 NA \n", "4 0 ptca 292 52 M:L;>@H \n", "\n", " language1 lex1 ps1 nu1 gn1 number1 pdp1 prs_ps1 prs_nu1 \\\n", "0 Hebrew [ unknown sg m 3739 verb unknown unknown \n", "4 Hebrew ML>[ unknown sg f 4604 verb unknown unknown \n", "\n", " prs_gn1 rank_occ1 sp1 st1 vs1 vt1 course approved \\\n", "0 unknown 7211 verb NaN qal impf NaN \n", "1 unknown 12851 verb NaN piel perf NaN \n", "2 m 12851 verb NaN piel perf NaN \n", "3 unknown 472 verb a qal ptca NaN \n", "4 unknown 766 verb a qal ptca NaN \n", "\n", " regular verbs only no suffix transposition paragogic nun \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "\n", " PielPualHitpael without DF should be excluded ambiguity not solved \\\n", "0 NaN x NaN \n", "1 NaN x x \n", "2 NaN x x \n", "3 NaN x x \n", "4 NaN x x \n", "\n", " ketiv-qere quiz day teaching days/weeks select learned vocab \n", "0 NaN NaN NaN NaN 200.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN 200.0 \n", "4 NaN NaN NaN NaN 200.0 " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyFirstVersion=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_OTST551_Heb-I-II-III_verbal-morphology_selection_of_2.xlsx')\n", "BHSallVerbalMorphologyFirstVersion.head()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tense_counts= BHSallVerbalMorphologyFirstVersion['vt1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "tense_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "ps_counts= BHSallVerbalMorphologyFirstVersion['ps1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "ps_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall PS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "gn_counts= BHSallVerbalMorphologyFirstVersion['gn1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "gn_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall GN Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vc_counts= BHSallVerbalMorphologyFirstVersion['bol_dict_vc1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vc_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VC Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vs_counts= BHSallVerbalMorphologyFirstVersion['vs1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vs_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Retrieving All Verbal Forms" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2023-01-16T22:42:59.491507Z", "start_time": "2023-01-16T22:42:52.195326Z" } }, "outputs": [], "source": [ "AllVerbs='''\n", "word bol_monad_num* bol_qere_presence* bol_lexeme_occurrences* bol_vt* dagesh* lex* number* vbe* vbs* uvf* prs* pfm* nme* freq_occ* freq_lex* st* rank_occ* bol_dict_abc* bol_dict_HebArm* bol_bhsa_word_order* bol_dict_vc* ps* nu* gn* vt* vs prs_nu* prs_ps* prs_gn* sp=verb pdp* bol_dict_EN* g_word_noaccent* language* \n", "\n", "'''\n", "AllVerbs = BHSa4c.search(AllVerbs)\n", "BHSa4c.table(AllVerbs, start=1, end=2, multiFeatures=True, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T19:51:07.031470Z", "start_time": "2022-06-02T19:50:56.289207Z" } }, "outputs": [], "source": [ "BHSa4c.export(AllVerbs, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_all_verb-morphology.tsv')" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperf
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperf
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptca
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayq
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpf
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 \n", "0 NaN absent qal perf \n", "1 H absent qal perf \n", "2 NaN absent piel ptca \n", "3 NaN absent qal wayq \n", "4 NaN absent qal impf " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "BHSallVerbalMorphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/BHSa4c_BOL_all_verb-morphology.tsv', delimiter='\\t', encoding='utf-16')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['ii-guttural, iii-aleph', 'i-guttural, iii-hey', 'i-guttural, ii-guttural', 'i-aleph', 'i-guttural, ii-guttural, iii-hey', 'ii-waw', 'regular', 'iii-hey', 'iii-aleph', 'ii-guttural, iii-guttural', 'i-waw, iii-aleph', 'i-guttural, ii-waw, iii-guttural', 'i-nun', 'ii-guttural', 'i-guttural, ii-waw', 'i-guttural', 'ii-guttural, iii-hey', 'iii-guttural', 'i-waw', 'i-nun, iii-guttural', 'ii-yod', 'geminate', 'i-nun, ii-waw, iii-guttural', 'ii-waw, iii-aleph', 'i-waw, iii-guttural', 'i-guttural, iii-aleph', 'i-waw, ii-guttural, iii-aleph', 'i-nun, iii-aleph', 'i-guttural, ii-guttural, geminate', 'i-yod', 'i-nun, ii-waw', 'i-nun, iii-hey', 'i-guttural, geminate', 'i-nun, ii-guttural', 'i-guttural, ii-yod', 'i-waw, ii-guttural', '4 root verb', 'ii-guttural, geminate', 'i-aleph, iii-hey', 'i-guttural, iii-guttural', 'i-nun, ii-guttural, iii-hey', 'ii-waw, iii-guttural', 'i-waw, iii-hey', 'i-nun, geminate', 'i-waw, ii-guttural, iii-hey', 'ii-yod, iii-guttural', 'ii-yod, iii-aleph', 'i-nun, ii-waw, iii-aleph', 'i-waw, geminate', 'i-guttural, ii-guttural, iii-guttural', 'i-nun, ii-guttural, geminate', 'i-yod, geminate', 'i-waw, ii-guttural, iii-guttural', 'i-nun, ii-yod', nan]\n" ] } ], "source": [ "vc=BHSallVerbalMorphology.bol_dict_vc1.unique().tolist()\n", "print(vc)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['perf', 'ptca', 'wayq', 'juss', 'impf', 'infc', 'impv', 'infa', 'ptcp', 'coho']\n" ] } ], "source": [ "vt=BHSallVerbalMorphology.bol_vt1.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['qal', 'piel', 'hif', 'nif', 'pual', 'hit', 'hof', 'hsht', 'pasq', 'hotp', 'nit', 'poal', 'poel', 'htpo', 'peal', 'tif', 'etpa', 'pael', 'haf', 'htpe', 'htpa', 'peil', 'etpe', 'afel', 'shaf']\n" ] } ], "source": [ "vs=BHSallVerbalMorphology.vs1.unique().tolist()\n", "print(vs)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Adding paragogic Nun as a data category" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[nan, 'H', 'W', 'TJ', 'WN', 'TM', 'NH', 'T', 'T=', 'J', 'H=', 'NW', 'TN', 'JN', 'TWN', 'N>', 'T==', 'N']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.vbe1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1
22673226741_Samuel114141814wordתִּשְׁתַּכָּרִ֑ין141814qal: be, become drunk; pi: make drunk; hit: be...שׁכר7728iii-guttural181418130impfDL_DF_DF181T.IC:T.AK.@RIJNfHebrewCKR[absentsg278verbTabsentunknownunknownunknownp212851verbNaNabsentJNHThitimpf
3834038341Isaiah4510228041wordתְּחִילִֽין׃ ס228041qal: be in labour, be in labor, be in pain; wr...חיל I2321i-guttural, ii-yod432280400impfDL401T.:XIJLIJNfHebrewXJL[absentsg15972verbTabsentunknownunknownunknownp212851verbNaNabsentJNabsentqalimpf
4302843029Jeremiah3122251047wordתִּתְחַמָּקִ֔ין251047qal: turn away; hit: turn hither and thither;חמק2455i-guttural22510460impfDL_DF21T.IT:XAM.@QIJNfHebrewXMQ[absentsg16047verbTabsentunknownunknownunknownp212851verbNaNabsentJNHThitimpf
6395463955Ruth28356401wordתִדְבָּקִ֖ין356401qal: stick, cling to; pu: be joined together; ...דבק1613regular543564000impf_DL542TID:B.@QIJNfHebrewDBQ[absentsg610verbTabsentunknownunknownunknownp29178verbNaNabsentJNabsentqalimpf
6403564036Ruth221356720wordתִּדְבָּקִ֔ין356720qal: stick, cling to; pu: be joined together; ...דבק1613regular543567190impfDL_DF542T.ID:B.@QIJNfHebrewDBQ[absentsg929verbTabsentunknownunknownunknownp29178verbNaNabsentJNabsentqalimpf
6406564066Ruth34356851wordתַּעֲשִֽׂין׃356851qal: do, make; ni: be made, done; pi: press, s...עשׂה6118i-guttural, iii-hey26293568500jussDL26291T.A<:AFIJNfHebrew<FH[absentsg1060verbTabsentunknownunknownunknownp212851verbNaNabsentJNabsentqalimpf
6412964130Ruth318357105wordתֵּֽדְעִ֔ין357105qal: know; notice; learn; ni: make oneself kno...ידע2947i-waw, iii-guttural9443571040impfDL9441T.;D:<IJNfHebrewJD<[absentsg1314verbTabsentunknownunknownunknownp212851verbNaNabsentJNabsentqalimpf
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "22673 22674 1_Samuel 1 14 141814 word תִּשְׁתַּכָּרִ֑ין \n", "38340 38341 Isaiah 45 10 228041 word תְּחִילִֽין׃ ס \n", "43028 43029 Jeremiah 31 22 251047 word תִּתְחַמָּקִ֔ין \n", "63954 63955 Ruth 2 8 356401 word תִדְבָּקִ֖ין \n", "64035 64036 Ruth 2 21 356720 word תִּדְבָּקִ֔ין \n", "64065 64066 Ruth 3 4 356851 word תַּעֲשִֽׂין׃ \n", "64129 64130 Ruth 3 18 357105 word תֵּֽדְעִ֔ין \n", "\n", " bol_bhsa_word_order1 \\\n", "22673 141814 \n", "38340 228041 \n", "43028 251047 \n", "63954 356401 \n", "64035 356720 \n", "64065 356851 \n", "64129 357105 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "22673 qal: be, become drunk; pi: make drunk; hit: be... שׁכר \n", "38340 qal: be in labour, be in labor, be in pain; wr... חיל I \n", "43028 qal: turn away; hit: turn hither and thither; חמק \n", "63954 qal: stick, cling to; pu: be joined together; ... דבק \n", "64035 qal: stick, cling to; pu: be joined together; ... דבק \n", "64065 qal: do, make; ni: be made, done; pi: press, s... עשׂה \n", "64129 qal: know; notice; learn; ni: make oneself kno... ידע \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "22673 7728 iii-guttural 18 \n", "38340 2321 i-guttural, ii-yod 43 \n", "43028 2455 i-guttural 2 \n", "63954 1613 regular 54 \n", "64035 1613 regular 54 \n", "64065 6118 i-guttural, iii-hey 2629 \n", "64129 2947 i-waw, iii-guttural 944 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "22673 141813 0 impf DL_DF_DF 18 \n", "38340 228040 0 impf DL 40 \n", "43028 251046 0 impf DL_DF 2 \n", "63954 356400 0 impf _DL 54 \n", "64035 356719 0 impf DL_DF 54 \n", "64065 356850 0 juss DL 2629 \n", "64129 357104 0 impf DL 944 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "22673 1 T.IC:T.AK.@RIJN f Hebrew CKR[ absent sg 278 \n", "38340 1 T.:XIJLIJN f Hebrew XJL[ absent sg 15972 \n", "43028 1 T.IT:XAM.@QIJN f Hebrew XMQ[ absent sg 16047 \n", "63954 2 TID:B.@QIJN f Hebrew DBQ[ absent sg 610 \n", "64035 2 T.ID:B.@QIJN f Hebrew DBQ[ absent sg 929 \n", "64065 1 T.A<:AFIJN f Hebrew \n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNun
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun \n", "0 NaN absent qal perf False \n", "1 H absent qal perf False \n", "2 NaN absent piel ptca False \n", "3 NaN absent qal wayq False \n", "4 NaN absent qal impf False " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology['paragogicNun'] = ((BHSallVerbalMorphology['language1']=='Hebrew') \n", " & (\n", " (BHSallVerbalMorphology['vbe1']=='WN') \n", " | (BHSallVerbalMorphology['vbe1']=='JN') \n", " ) )\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNun
187188Genesis331231wordתְּמֻתֽוּן׃1231qal: die; pi: kill; hi: kill, put to death; ho...מות4054ii-waw83512310impfDL_DF8353T.:MUTW.NmHebrewMWT[absentpl1231verbTabsentunknownunknownunknownp27211verbNaNabsentWNabsentqalimpfTrue
190191Genesis341241wordתְּמֻתֽוּן׃1241qal: die; pi: kill; hi: kill, put to death; ho...מות4054ii-waw83512410impfDL_DF8353T.:MUTW.NmHebrewMWT[absentpl1241verbTabsentunknownunknownunknownp27211verbNaNabsentWNabsentqalimpfTrue
12891290Genesis18288300wordיַחְסְר֞וּן8300qal: lack, be lacking, decrease; pi: cause to ...חסר2534i-guttural2483000impfNaN241JAX:S:RW.NmHebrewXSR[absentpl8300verbJabsentunknownunknownunknownp312851verbNaNabsentWNabsentqalimpfTrue
12971298Genesis18298332wordיִמָּצְא֥וּן8332qal: find; ni: be found; hi: present;מצא4546iii-aleph45383320impfNaN4534JIM.@Y:>W.NmHebrewMY>[absentpl8332verbJabsentunknownunknownunknownp36060verbNaNabsentWNNnifimpfTrue
13031304Genesis18308353wordיִמָּצְא֥וּן8353qal: find; ni: be found; hi: present;מצא4546iii-aleph45383530impfNaN4534JIM.@Y:>W.NmHebrewMY>[absentpl8353verbJabsentunknownunknownunknownp36060verbNaNabsentWNNnifimpfTrue
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "187 188 Genesis 3 3 1231 word תְּמֻתֽוּן׃ 1231 \n", "190 191 Genesis 3 4 1241 word תְּמֻתֽוּן׃ 1241 \n", "1289 1290 Genesis 18 28 8300 word יַחְסְר֞וּן 8300 \n", "1297 1298 Genesis 18 29 8332 word יִמָּצְא֥וּן 8332 \n", "1303 1304 Genesis 18 30 8353 word יִמָּצְא֥וּן 8353 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "187 qal: die; pi: kill; hi: kill, put to death; ho... מות \n", "190 qal: die; pi: kill; hi: kill, put to death; ho... מות \n", "1289 qal: lack, be lacking, decrease; pi: cause to ... חסר \n", "1297 qal: find; ni: be found; hi: present; מצא \n", "1303 qal: find; ni: be found; hi: present; מצא \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "187 4054 ii-waw 835 1231 \n", "190 4054 ii-waw 835 1241 \n", "1289 2534 i-guttural 24 8300 \n", "1297 4546 iii-aleph 453 8332 \n", "1303 4546 iii-aleph 453 8353 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "187 0 impf DL_DF 835 3 \n", "190 0 impf DL_DF 835 3 \n", "1289 0 impf NaN 24 1 \n", "1297 0 impf NaN 453 4 \n", "1303 0 impf NaN 453 4 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "187 T.:MUTW.N m Hebrew MWT[ absent pl 1231 verb T \n", "190 T.:MUTW.N m Hebrew MWT[ absent pl 1241 verb T \n", "1289 JAX:S:RW.N m Hebrew XSR[ absent pl 8300 verb J \n", "1297 JIM.@Y:>W.N m Hebrew MY>[ absent pl 8332 verb J \n", "1303 JIM.@Y:>W.N m Hebrew MY>[ absent pl 8353 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "187 absent unknown unknown unknown p2 7211 verb NaN absent \n", "190 absent unknown unknown unknown p2 7211 verb NaN absent \n", "1289 absent unknown unknown unknown p3 12851 verb NaN absent \n", "1297 absent unknown unknown unknown p3 6060 verb NaN absent \n", "1303 absent unknown unknown unknown p3 6060 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun \n", "187 WN absent qal impf True \n", "190 WN absent qal impf True \n", "1289 WN absent qal impf True \n", "1297 WN N nif impf True \n", "1303 WN N nif impf True " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['paragogicNun']==True)].head()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "R 322\n", "S1 322\n", "S2 322\n", "S3 322\n", "NODE1 322\n", "TYPE1 322\n", "TEXT1 322\n", "bol_bhsa_word_order1 322\n", "bol_dict_EN1 322\n", "bol_dict_HebArm1 322\n", "bol_dict_abc1 322\n", "bol_dict_vc1 322\n", "bol_lexeme_occurrences1 322\n", "bol_monad_num1 322\n", "bol_qere_presence1 322\n", "bol_vt1 322\n", "dagesh1 125\n", "freq_lex1 322\n", "freq_occ1 322\n", "g_word_noaccent1 322\n", "gn1 322\n", "language1 322\n", "lex1 322\n", "nme1 322\n", "nu1 322\n", "number1 322\n", "pdp1 322\n", "pfm1 322\n", "prs1 322\n", "prs_gn1 322\n", "prs_nu1 322\n", "prs_ps1 322\n", "ps1 322\n", "rank_occ1 322\n", "sp1 322\n", "st1 0\n", "uvf1 322\n", "vbe1 322\n", "vbs1 322\n", "vs1 322\n", "vt1 322\n", "paragogicNun 322\n", "dtype: int64" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['paragogicNun']==True)].count()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Adding Emphatic Imperative as a data category" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[nan, 'H', 'W', 'TJ', 'WN', 'TM', 'NH', 'T', 'T=', 'J', 'H=', 'NW', 'TN', 'JN', 'TWN', 'N>', 'T==', 'N']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.vbe1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNun
730731Genesis1134996wordהָ֚בָה4996qal: give (impv), come on (interj);יהב2952i-waw, ii-guttural3449960impvNaN3412H@B@HmHebrewJHB[absentsg4996verbNaNabsentunknownunknownunknownp22761verbNaNabsentH=absentqalimpvFalse
736737Genesis1145020wordהָ֣בָה׀5020qal: give (impv), come on (interj);יהב2952i-waw, ii-guttural3450200impvNaN3412H@B@HmHebrewJHB[absentsg5020verbNaNabsentunknownunknownunknownp22761verbNaNabsentH=absentqalimpvFalse
749750Genesis1175085wordהָ֚בָה5085qal: give (impv), come on (interj);יהב2952i-waw, ii-guttural3450850impvNaN3412H@B@HmHebrewJHB[absentsg5085verbNaNabsentunknownunknownunknownp22761verbNaNabsentH=absentqalimpvFalse
10221023Genesis1596811wordקְחָ֥ה6811qal: take, grasp, seize; qal pass: take, grasp...לקח3831i-nun, iii-guttural96568110impvNaN9651Q:X@HmHebrewLQX[absentsg6811verbNaNabsentunknownunknownunknownp212851verbNaNabsentH=absentqalimpvFalse
14581459Genesis19329112wordלְכָ֨ה9112qal: go, walk; ni: be gone, fade; pi: go, walk...הלך1879i-waw154791120impvNaN154734L:K@HmHebrewHLK[absentsg9112verbNaNabsentunknownunknownunknownp21123verbNaNabsentH=absentqalimpvFalse
16351636Genesis212310032wordהִשָּׁ֨בְעָה10032ni: swear; hi: swear;שׁבע7526iii-guttural185100320impvNaN1855HIC.@B:<@HmHebrewCB<[absentsg10032verbHabsentunknownunknownunknownp25226verbNaNabsentH=NnifimpvFalse
21442145Genesis253112917wordמִכְרָ֥ה12917qal: sell, give in other hands; ni: be sold; h...מכר4239iii-guttural80129170impvNaN805MIK:R@HmHebrewMKR[absentsg12917verbNaNabsentunknownunknownunknownp25226verbNaNabsentH=absentqalimpvFalse
21492150Genesis253312940wordהִשָּׁ֤בְעָה12940ni: swear; hi: swear;שׁבע7526iii-guttural185129400impvNaN1855HIC.@B:<@HmHebrewCB<[absentsg12940verbHabsentunknownunknownunknownp25226verbNaNabsentH=NnifimpvFalse
23012302Genesis27313682wordצ֥וּדָה13682qal: hunt; pi: hunt;צוד6556ii-waw17136820impvNaN171YW.D@HmHebrewYWD[absentsg13682verbNaNabsentunknownunknownunknownp212851verbNaNabsentH=absentqalimpvFalse
23042305Genesis27413693wordהָבִ֥יאָה13693qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph2570136930impvNaN257010H@BIJ>@HmHebrewBW>[absentsg13693verbNaNabsentunknownunknownunknownp23149verbNaNabsentH=HhifimpvFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "730 731 Genesis 11 3 4996 word הָ֚בָה 4996 \n", "736 737 Genesis 11 4 5020 word הָ֣בָה׀ 5020 \n", "749 750 Genesis 11 7 5085 word הָ֚בָה 5085 \n", "1022 1023 Genesis 15 9 6811 word קְחָ֥ה 6811 \n", "1458 1459 Genesis 19 32 9112 word לְכָ֨ה 9112 \n", "1635 1636 Genesis 21 23 10032 word הִשָּׁ֨בְעָה 10032 \n", "2144 2145 Genesis 25 31 12917 word מִכְרָ֥ה 12917 \n", "2149 2150 Genesis 25 33 12940 word הִשָּׁ֤בְעָה 12940 \n", "2301 2302 Genesis 27 3 13682 word צ֥וּדָה 13682 \n", "2304 2305 Genesis 27 4 13693 word הָבִ֥יאָה 13693 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "730 qal: give (impv), come on (interj); יהב \n", "736 qal: give (impv), come on (interj); יהב \n", "749 qal: give (impv), come on (interj); יהב \n", "1022 qal: take, grasp, seize; qal pass: take, grasp... לקח \n", "1458 qal: go, walk; ni: be gone, fade; pi: go, walk... הלך \n", "1635 ni: swear; hi: swear; שׁבע \n", "2144 qal: sell, give in other hands; ni: be sold; h... מכר \n", "2149 ni: swear; hi: swear; שׁבע \n", "2301 qal: hunt; pi: hunt; צוד \n", "2304 qal: come, enter, go in; hi: bring; let come; ... בוא \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "730 2952 i-waw, ii-guttural 34 \n", "736 2952 i-waw, ii-guttural 34 \n", "749 2952 i-waw, ii-guttural 34 \n", "1022 3831 i-nun, iii-guttural 965 \n", "1458 1879 i-waw 1547 \n", "1635 7526 iii-guttural 185 \n", "2144 4239 iii-guttural 80 \n", "2149 7526 iii-guttural 185 \n", "2301 6556 ii-waw 17 \n", "2304 889 ii-waw, iii-aleph 2570 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "730 4996 0 impv NaN 34 \n", "736 5020 0 impv NaN 34 \n", "749 5085 0 impv NaN 34 \n", "1022 6811 0 impv NaN 965 \n", "1458 9112 0 impv NaN 1547 \n", "1635 10032 0 impv NaN 185 \n", "2144 12917 0 impv NaN 80 \n", "2149 12940 0 impv NaN 185 \n", "2301 13682 0 impv NaN 17 \n", "2304 13693 0 impv NaN 2570 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "730 12 H@B@H m Hebrew JHB[ absent sg 4996 \n", "736 12 H@B@H m Hebrew JHB[ absent sg 5020 \n", "749 12 H@B@H m Hebrew JHB[ absent sg 5085 \n", "1022 1 Q:X@H m Hebrew LQX[ absent sg 6811 \n", "1458 34 L:K@H m Hebrew HLK[ absent sg 9112 \n", "1635 5 HIC.@B:<@H m Hebrew CB<[ absent sg 10032 \n", "2144 5 MIK:R@H m Hebrew MKR[ absent sg 12917 \n", "2149 5 HIC.@B:<@H m Hebrew CB<[ absent sg 12940 \n", "2301 1 YW.D@H m Hebrew YWD[ absent sg 13682 \n", "2304 10 H@BIJ>@H m Hebrew BW>[ absent sg 13693 \n", "\n", " pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "730 verb NaN absent unknown unknown unknown p2 2761 verb NaN \n", "736 verb NaN absent unknown unknown unknown p2 2761 verb NaN \n", "749 verb NaN absent unknown unknown unknown p2 2761 verb NaN \n", "1022 verb NaN absent unknown unknown unknown p2 12851 verb NaN \n", "1458 verb NaN absent unknown unknown unknown p2 1123 verb NaN \n", "1635 verb H absent unknown unknown unknown p2 5226 verb NaN \n", "2144 verb NaN absent unknown unknown unknown p2 5226 verb NaN \n", "2149 verb H absent unknown unknown unknown p2 5226 verb NaN \n", "2301 verb NaN absent unknown unknown unknown p2 12851 verb NaN \n", "2304 verb NaN absent unknown unknown unknown p2 3149 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \n", "730 absent H= absent qal impv False \n", "736 absent H= absent qal impv False \n", "749 absent H= absent qal impv False \n", "1022 absent H= absent qal impv False \n", "1458 absent H= absent qal impv False \n", "1635 absent H= N nif impv False \n", "2144 absent H= absent qal impv False \n", "2149 absent H= N nif impv False \n", "2301 absent H= absent qal impv False \n", "2304 absent H= H hif impv False " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['language1']=='Hebrew') \n", " & (BHSallVerbalMorphology['vbe1']=='H=')\n", " & (BHSallVerbalMorphology['vt1']=='impv')\n", " ].head(10)\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "R 306\n", "S1 306\n", "S2 306\n", "S3 306\n", "NODE1 306\n", "TYPE1 306\n", "TEXT1 306\n", "bol_bhsa_word_order1 306\n", "bol_dict_EN1 306\n", "bol_dict_HebArm1 306\n", "bol_dict_abc1 306\n", "bol_dict_vc1 306\n", "bol_lexeme_occurrences1 306\n", "bol_monad_num1 306\n", "bol_qere_presence1 306\n", "bol_vt1 306\n", "dagesh1 35\n", "freq_lex1 306\n", "freq_occ1 306\n", "g_word_noaccent1 306\n", "gn1 306\n", "language1 306\n", "lex1 306\n", "nme1 306\n", "nu1 306\n", "number1 306\n", "pdp1 306\n", "pfm1 5\n", "prs1 306\n", "prs_gn1 306\n", "prs_nu1 306\n", "prs_ps1 306\n", "ps1 306\n", "rank_occ1 306\n", "sp1 306\n", "st1 0\n", "uvf1 306\n", "vbe1 306\n", "vbs1 306\n", "vs1 306\n", "vt1 306\n", "paragogicNun 306\n", "dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['language1']=='Hebrew') \n", " & (BHSallVerbalMorphology['vbe1']=='H=')\n", " & (BHSallVerbalMorphology['vt1']=='impv')\n", " ].count()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpv
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \n", "0 NaN absent qal perf False False \n", "1 H absent qal perf False False \n", "2 NaN absent piel ptca False False \n", "3 NaN absent qal wayq False False \n", "4 NaN absent qal impf False False " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology['emphaticImpv'] = ((BHSallVerbalMorphology['language1']=='Hebrew') \n", " & (BHSallVerbalMorphology['vbe1']=='H=')\n", " & (BHSallVerbalMorphology['vt1']=='impv'))\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpv
730731Genesis1134996wordהָ֚בָה4996qal: give (impv), come on (interj);יהב2952i-waw, ii-guttural3449960impvNaN3412H@B@HmHebrewJHB[absentsg4996verbNaNabsentunknownunknownunknownp22761verbNaNabsentH=absentqalimpvFalseTrue
736737Genesis1145020wordהָ֣בָה׀5020qal: give (impv), come on (interj);יהב2952i-waw, ii-guttural3450200impvNaN3412H@B@HmHebrewJHB[absentsg5020verbNaNabsentunknownunknownunknownp22761verbNaNabsentH=absentqalimpvFalseTrue
749750Genesis1175085wordהָ֚בָה5085qal: give (impv), come on (interj);יהב2952i-waw, ii-guttural3450850impvNaN3412H@B@HmHebrewJHB[absentsg5085verbNaNabsentunknownunknownunknownp22761verbNaNabsentH=absentqalimpvFalseTrue
10221023Genesis1596811wordקְחָ֥ה6811qal: take, grasp, seize; qal pass: take, grasp...לקח3831i-nun, iii-guttural96568110impvNaN9651Q:X@HmHebrewLQX[absentsg6811verbNaNabsentunknownunknownunknownp212851verbNaNabsentH=absentqalimpvFalseTrue
14581459Genesis19329112wordלְכָ֨ה9112qal: go, walk; ni: be gone, fade; pi: go, walk...הלך1879i-waw154791120impvNaN154734L:K@HmHebrewHLK[absentsg9112verbNaNabsentunknownunknownunknownp21123verbNaNabsentH=absentqalimpvFalseTrue
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "730 731 Genesis 11 3 4996 word הָ֚בָה 4996 \n", "736 737 Genesis 11 4 5020 word הָ֣בָה׀ 5020 \n", "749 750 Genesis 11 7 5085 word הָ֚בָה 5085 \n", "1022 1023 Genesis 15 9 6811 word קְחָ֥ה 6811 \n", "1458 1459 Genesis 19 32 9112 word לְכָ֨ה 9112 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "730 qal: give (impv), come on (interj); יהב \n", "736 qal: give (impv), come on (interj); יהב \n", "749 qal: give (impv), come on (interj); יהב \n", "1022 qal: take, grasp, seize; qal pass: take, grasp... לקח \n", "1458 qal: go, walk; ni: be gone, fade; pi: go, walk... הלך \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "730 2952 i-waw, ii-guttural 34 \n", "736 2952 i-waw, ii-guttural 34 \n", "749 2952 i-waw, ii-guttural 34 \n", "1022 3831 i-nun, iii-guttural 965 \n", "1458 1879 i-waw 1547 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "730 4996 0 impv NaN 34 \n", "736 5020 0 impv NaN 34 \n", "749 5085 0 impv NaN 34 \n", "1022 6811 0 impv NaN 965 \n", "1458 9112 0 impv NaN 1547 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "730 12 H@B@H m Hebrew JHB[ absent sg 4996 \n", "736 12 H@B@H m Hebrew JHB[ absent sg 5020 \n", "749 12 H@B@H m Hebrew JHB[ absent sg 5085 \n", "1022 1 Q:X@H m Hebrew LQX[ absent sg 6811 \n", "1458 34 L:K@H m Hebrew HLK[ absent sg 9112 \n", "\n", " pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "730 verb NaN absent unknown unknown unknown p2 2761 verb NaN \n", "736 verb NaN absent unknown unknown unknown p2 2761 verb NaN \n", "749 verb NaN absent unknown unknown unknown p2 2761 verb NaN \n", "1022 verb NaN absent unknown unknown unknown p2 12851 verb NaN \n", "1458 verb NaN absent unknown unknown unknown p2 1123 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \n", "730 absent H= absent qal impv False True \n", "736 absent H= absent qal impv False True \n", "749 absent H= absent qal impv False True \n", "1022 absent H= absent qal impv False True \n", "1458 absent H= absent qal impv False True " ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['emphaticImpv']==True)].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Adding Hitpael Transposition as a data category" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['absent', 'M', 'J', 'T=', nan, 'N', 'H', 'T', '>', 'L']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.pfm1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpv
1268512686Numbers161380304wordתִשְׂתָּרֵ֥ר80304qal: rule; hit: play the ruler;שׂרר8230ii-guttural, geminate6803030impf_DL61TIF:T.@R;RmHebrewFRR[absentsg10694verbTabsentunknownunknownunknownp212851verbNaNabsentNaNHThitimpfFalseFalse
1268612687Numbers161380307wordהִשְׂתָּרֵֽר׃80307qal: rule; hit: play the ruler;שׂרר8230ii-guttural, geminate6803060infa_DL61HIF:T.@R;RunknownHebrewFRR[NaNunknown10697advbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfaFalseFalse
22673226741_Samuel114141814wordתִּשְׁתַּכָּרִ֑ין141814qal: be, become drunk; pi: make drunk; hit: be...שׁכר7728iii-guttural181418130impfDL_DF_DF181T.IC:T.AK.@RIJNfHebrewCKR[absentsg278verbTabsentunknownunknownunknownp212851verbNaNabsentJNHThitimpfTrueFalse
25102251031_Samuel2116154738wordהִשְׁתַּגֵּ֖עַ154738pu: be mad; hit: behave as a madman;שׁגע7553iii-guttural71547370infc_DL71HIC:T.AG.;<AunknownHebrewCG<[NaNunknown13202verbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfcFalseFalse
25727257281_Samuel2619158045wordהִסְתַּפֵּ֜חַ158045qal: attach to; ni: attach oneself to; pi: joi...ספח5454iii-guttural51580440infc_DL51HIS:T.AP.;XAunknownHebrewSPX[NaNunknown16509verbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfcFalseFalse
28669286702_Samuel2224174539wordאֶשְׁתַּמְּרָ֖ה174539qal: keep watch, guard; ni: be guarded; beware...שׁמר7869iii-guttural4681745380wayq_DL4681>EC:T.AM.:R@HunknownHebrewCMR[absentsg14074verb>absentunknownunknownunknownp112851verbNaNabsentH=HThitwayqFalseFalse
30650306511_Kings142187657wordהִשְׁתַּנִּ֔ית187657qal: change; repeat; differ; ni: be repeated; ...שׁנה7900iii-hey251876560perf_DL251HIC:T.AN.IJTfHebrewCNH[absentsg11580verbabsentabsentunknownunknownunknownp212851verbNaNabsentT=HThitperfFalseFalse
3682436825Isaiah2820221177wordהִשְׂתָּרֵ֑עַ221177qal: deformed; hit: stretch oneself;שׂרע8220ii-guttural, iii-guttural32211760infc_DL31HIF:T.@R;<AunknownHebrewFR<[NaNunknown9108verbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfcFalseFalse
3689536896Isaiah299221496wordהִשְׁתַּֽעַשְׁע֖וּ221496qal: be pasted together; hit: be pasted togeth...שׁעע II7926ii-guttural, geminate32214950impv_DL31HIC:T.A<AC:<W.mHebrewC<<=[absentpl9427verbNaNabsentunknownunknownunknownp212851verbNaNabsentWHThitimpvFalseFalse
3692836929Isaiah2914221622wordתִּסְתַּתָּֽר׃ ס221622ni: (intransitive) conceal, hide; pi: hide; pu...סתר5502iii-guttural812216210impfDL_DF_DF811T.IS:T.AT.@RfHebrewSTR[absentsg9553verbT=absentunknownunknownunknownp312851verbNaNabsentNaNHThitimpfFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "12685 12686 Numbers 16 13 80304 word תִשְׂתָּרֵ֥ר \n", "12686 12687 Numbers 16 13 80307 word הִשְׂתָּרֵֽר׃ \n", "22673 22674 1_Samuel 1 14 141814 word תִּשְׁתַּכָּרִ֑ין \n", "25102 25103 1_Samuel 21 16 154738 word הִשְׁתַּגֵּ֖עַ \n", "25727 25728 1_Samuel 26 19 158045 word הִסְתַּפֵּ֜חַ \n", "28669 28670 2_Samuel 22 24 174539 word אֶשְׁתַּמְּרָ֖ה \n", "30650 30651 1_Kings 14 2 187657 word הִשְׁתַּנִּ֔ית \n", "36824 36825 Isaiah 28 20 221177 word הִשְׂתָּרֵ֑עַ \n", "36895 36896 Isaiah 29 9 221496 word הִשְׁתַּֽעַשְׁע֖וּ \n", "36928 36929 Isaiah 29 14 221622 word תִּסְתַּתָּֽר׃ ס \n", "\n", " bol_bhsa_word_order1 \\\n", "12685 80304 \n", "12686 80307 \n", "22673 141814 \n", "25102 154738 \n", "25727 158045 \n", "28669 174539 \n", "30650 187657 \n", "36824 221177 \n", "36895 221496 \n", "36928 221622 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "12685 qal: rule; hit: play the ruler; שׂרר \n", "12686 qal: rule; hit: play the ruler; שׂרר \n", "22673 qal: be, become drunk; pi: make drunk; hit: be... שׁכר \n", "25102 pu: be mad; hit: behave as a madman; שׁגע \n", "25727 qal: attach to; ni: attach oneself to; pi: joi... ספח \n", "28669 qal: keep watch, guard; ni: be guarded; beware... שׁמר \n", "30650 qal: change; repeat; differ; ni: be repeated; ... שׁנה \n", "36824 qal: deformed; hit: stretch oneself; שׂרע \n", "36895 qal: be pasted together; hit: be pasted togeth... שׁעע II \n", "36928 ni: (intransitive) conceal, hide; pi: hide; pu... סתר \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "12685 8230 ii-guttural, geminate 6 \n", "12686 8230 ii-guttural, geminate 6 \n", "22673 7728 iii-guttural 18 \n", "25102 7553 iii-guttural 7 \n", "25727 5454 iii-guttural 5 \n", "28669 7869 iii-guttural 468 \n", "30650 7900 iii-hey 25 \n", "36824 8220 ii-guttural, iii-guttural 3 \n", "36895 7926 ii-guttural, geminate 3 \n", "36928 5502 iii-guttural 81 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "12685 80303 0 impf _DL 6 \n", "12686 80306 0 infa _DL 6 \n", "22673 141813 0 impf DL_DF_DF 18 \n", "25102 154737 0 infc _DL 7 \n", "25727 158044 0 infc _DL 5 \n", "28669 174538 0 wayq _DL 468 \n", "30650 187656 0 perf _DL 25 \n", "36824 221176 0 infc _DL 3 \n", "36895 221495 0 impv _DL 3 \n", "36928 221621 0 impf DL_DF_DF 81 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 \\\n", "12685 1 TIF:T.@R;R m Hebrew FRR[ absent sg \n", "12686 1 HIF:T.@R;R unknown Hebrew FRR[ NaN unknown \n", "22673 1 T.IC:T.AK.@RIJN f Hebrew CKR[ absent sg \n", "25102 1 HIC:T.AG.;EC:T.AM.:R@H unknown Hebrew CMR[ absent sg \n", "30650 1 HIC:T.AN.IJT f Hebrew CNH[ absent sg \n", "36824 1 HIF:T.@R; absent unknown unknown unknown p1 \n", "30650 11580 verb absent absent unknown unknown unknown p2 \n", "36824 9108 verb NaN absent unknown unknown unknown unknown \n", "36895 9427 verb NaN absent unknown unknown unknown p2 \n", "36928 9553 verb T= absent unknown unknown unknown p3 \n", "\n", " rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "12685 12851 verb NaN absent NaN HT hit impf False \n", "12686 12851 verb a absent NaN HT hit infa False \n", "22673 12851 verb NaN absent JN HT hit impf True \n", "25102 12851 verb a absent NaN HT hit infc False \n", "25727 12851 verb a absent NaN HT hit infc False \n", "28669 12851 verb NaN absent H= HT hit wayq False \n", "30650 12851 verb NaN absent T= HT hit perf False \n", "36824 12851 verb a absent NaN HT hit infc False \n", "36895 12851 verb NaN absent W HT hit impv False \n", "36928 12851 verb NaN absent NaN HT hit impf False \n", "\n", " emphaticImpv \n", "12685 False \n", "12686 False \n", "22673 False \n", "25102 False \n", "25727 False \n", "28669 False \n", "30650 False \n", "36824 False \n", "36895 False \n", "36928 False " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[ (BHSallVerbalMorphology['language1']=='Hebrew') \n", " & (BHSallVerbalMorphology['vbs1']=='HT')\n", " & (BHSallVerbalMorphology['lex1'].str.contains('^[FCSY]'))\n", " & (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[TJN>].*[FCSY].[T]'))\n", " | (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[H].*[FCSY].[T]'))\n", " )\n", " ].head(10)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTransposition
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology['Transposition'] = (\n", " (BHSallVerbalMorphology['language1']=='Hebrew') \n", " & (BHSallVerbalMorphology['vbs1']=='HT')\n", " & (BHSallVerbalMorphology['lex1'].str.contains('^[FCSY]'))\n", " & (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[TJN>].*[FCSY].[T]'))\n", " | (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[H].*[FCSY].[T]'))\n", " )\n", " )\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTransposition
1268512686Numbers161380304wordתִשְׂתָּרֵ֥ר80304qal: rule; hit: play the ruler;שׂרר8230ii-guttural, geminate6803030impf_DL61TIF:T.@R;RmHebrewFRR[absentsg10694verbTabsentunknownunknownunknownp212851verbNaNabsentNaNHThitimpfFalseFalseTrue
1268612687Numbers161380307wordהִשְׂתָּרֵֽר׃80307qal: rule; hit: play the ruler;שׂרר8230ii-guttural, geminate6803060infa_DL61HIF:T.@R;RunknownHebrewFRR[NaNunknown10697advbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfaFalseFalseTrue
22673226741_Samuel114141814wordתִּשְׁתַּכָּרִ֑ין141814qal: be, become drunk; pi: make drunk; hit: be...שׁכר7728iii-guttural181418130impfDL_DF_DF181T.IC:T.AK.@RIJNfHebrewCKR[absentsg278verbTabsentunknownunknownunknownp212851verbNaNabsentJNHThitimpfTrueFalseTrue
25102251031_Samuel2116154738wordהִשְׁתַּגֵּ֖עַ154738pu: be mad; hit: behave as a madman;שׁגע7553iii-guttural71547370infc_DL71HIC:T.AG.;<AunknownHebrewCG<[NaNunknown13202verbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfcFalseFalseTrue
25727257281_Samuel2619158045wordהִסְתַּפֵּ֜חַ158045qal: attach to; ni: attach oneself to; pi: joi...ספח5454iii-guttural51580440infc_DL51HIS:T.AP.;XAunknownHebrewSPX[NaNunknown16509verbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHThitinfcFalseFalseTrue
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "12685 12686 Numbers 16 13 80304 word תִשְׂתָּרֵ֥ר \n", "12686 12687 Numbers 16 13 80307 word הִשְׂתָּרֵֽר׃ \n", "22673 22674 1_Samuel 1 14 141814 word תִּשְׁתַּכָּרִ֑ין \n", "25102 25103 1_Samuel 21 16 154738 word הִשְׁתַּגֵּ֖עַ \n", "25727 25728 1_Samuel 26 19 158045 word הִסְתַּפֵּ֜חַ \n", "\n", " bol_bhsa_word_order1 \\\n", "12685 80304 \n", "12686 80307 \n", "22673 141814 \n", "25102 154738 \n", "25727 158045 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "12685 qal: rule; hit: play the ruler; שׂרר \n", "12686 qal: rule; hit: play the ruler; שׂרר \n", "22673 qal: be, become drunk; pi: make drunk; hit: be... שׁכר \n", "25102 pu: be mad; hit: behave as a madman; שׁגע \n", "25727 qal: attach to; ni: attach oneself to; pi: joi... ספח \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "12685 8230 ii-guttural, geminate 6 \n", "12686 8230 ii-guttural, geminate 6 \n", "22673 7728 iii-guttural 18 \n", "25102 7553 iii-guttural 7 \n", "25727 5454 iii-guttural 5 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "12685 80303 0 impf _DL 6 \n", "12686 80306 0 infa _DL 6 \n", "22673 141813 0 impf DL_DF_DF 18 \n", "25102 154737 0 infc _DL 7 \n", "25727 158044 0 infc _DL 5 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 \\\n", "12685 1 TIF:T.@R;R m Hebrew FRR[ absent sg \n", "12686 1 HIF:T.@R;R unknown Hebrew FRR[ NaN unknown \n", "22673 1 T.IC:T.AK.@RIJN f Hebrew CKR[ absent sg \n", "25102 1 HIC:T.AG.;', 'T==', 'N']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.vbe1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTransposition
30643065Genesis32617528wordאֶשְׁלְחָה֙17528qal: send; ni: be sent; pi: let go; stretch ou...שׁלח7754iii-guttural847175270wayqNaN8479>EC:L:X@HunknownHebrewCLX[absentsg17528verb>absentunknownunknownunknownp13421verbNaNabsentH=absentqalwayqFalseFalseFalse
39603961Genesis411122547wordנַּֽחַלְמָ֥ה22547qal: become strong; dream; hi: make strong;חלם2384i-guttural29225460wayqDF291N.AXAL:M@HunknownHebrewXLM[absentpl22547verbNabsentunknownunknownunknownp112851verbNaNabsentH=absentqalwayqFalseFalseFalse
43354336Genesis432124560wordנִּפְתְּחָה֙24560qal: open; ni: be opened; pi: loose, free; hit...פתח I6478iii-guttural135245590wayqDF_DL1352N.IP:T.:X@HunknownHebrewPTX[absentpl24560verbNabsentunknownunknownunknownp19178verbNaNabsentH=absentqalwayqFalseFalseFalse
1193611937Numbers81975564wordאֶתְּנָ֨ה75564qal: give, place; ni: be given, put; ho: be gi...נתן5268i-nun2010755630wayqNaN201037>ET.:N@HunknownHebrewNTN[absentsg5954verb>absentunknownunknownunknownp11046verbNaNabsentH=absentqalwayqFalseFalseFalse
2062320624Judges69130600wordאֶתְּנָ֥ה130600qal: give, place; ni: be given, put; ho: be gi...נתן5268i-nun20101305990wayqNaN201037>ET.:N@HunknownHebrewNTN[absentsg3149verb>absentunknownunknownunknownp11046verbNaNabsentH=absentqalwayqFalseFalseFalse
2062420625Judges610130605wordאֹמְרָ֣ה130605qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph53071306040wayqNaN530745>OM:R@HunknownHebrew>MR[absentsg3154verb>absentunknownunknownunknownp1868verbNaNabsentH=absentqalwayqFalseFalseFalse
2126521266Judges1012134355wordאֹושִׁ֥יעָה134355ni: be saved; hi: save;ישׁע3352i-waw, iii-guttural2051343540wayqNaN2051>OWCIJ<@HunknownHebrewJC<[absentsg6904verb>absentunknownunknownunknownp112851verbNaNabsentH=HhifwayqFalseFalseFalse
2146921470Judges123135442wordאָשִׂ֨ימָה135442qal: set, place; hi: set, make into; ho: be put;שׂים8127ii-yod5831354410wayqNaN5834>@FIJM@HunknownHebrewFJM[absentsg7991verb>absentunknownunknownunknownp16060verbNaNabsentH=absentqalwayqFalseFalseFalse
2147021471Judges123135447wordאֶעְבְּרָה֙135447qal: pass over, transgress; ni: be crossed; pi...עבר I5539i-guttural5481354460wayq_DL5489>E<:B.:R@HunknownHebrew<BR[absentsg7996verb>absentunknownunknownunknownp13421verbNaNabsentH=absentqalwayqFalseFalseFalse
22844228451_Samuel228142673wordאֶתְּנָה֙142673qal: give, place; ni: be given, put; ho: be gi...נתן5268i-nun20101426720wayqNaN201037>ET.:N@HunknownHebrewNTN[absentsg1137verb>absentunknownunknownunknownp11046verbNaNabsentH=absentqalwayqFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "3064 3065 Genesis 32 6 17528 word אֶשְׁלְחָה֙ \n", "3960 3961 Genesis 41 11 22547 word נַּֽחַלְמָ֥ה \n", "4335 4336 Genesis 43 21 24560 word נִּפְתְּחָה֙ \n", "11936 11937 Numbers 8 19 75564 word אֶתְּנָ֨ה \n", "20623 20624 Judges 6 9 130600 word אֶתְּנָ֥ה \n", "20624 20625 Judges 6 10 130605 word אֹמְרָ֣ה \n", "21265 21266 Judges 10 12 134355 word אֹושִׁ֥יעָה \n", "21469 21470 Judges 12 3 135442 word אָשִׂ֨ימָה \n", "21470 21471 Judges 12 3 135447 word אֶעְבְּרָה֙ \n", "22844 22845 1_Samuel 2 28 142673 word אֶתְּנָה֙ \n", "\n", " bol_bhsa_word_order1 \\\n", "3064 17528 \n", "3960 22547 \n", "4335 24560 \n", "11936 75564 \n", "20623 130600 \n", "20624 130605 \n", "21265 134355 \n", "21469 135442 \n", "21470 135447 \n", "22844 142673 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "3064 qal: send; ni: be sent; pi: let go; stretch ou... שׁלח \n", "3960 qal: become strong; dream; hi: make strong; חלם \n", "4335 qal: open; ni: be opened; pi: loose, free; hit... פתח I \n", "11936 qal: give, place; ni: be given, put; ho: be gi... נתן \n", "20623 qal: give, place; ni: be given, put; ho: be gi... נתן \n", "20624 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "21265 ni: be saved; hi: save; ישׁע \n", "21469 qal: set, place; hi: set, make into; ho: be put; שׂים \n", "21470 qal: pass over, transgress; ni: be crossed; pi... עבר I \n", "22844 qal: give, place; ni: be given, put; ho: be gi... נתן \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "3064 7754 iii-guttural 847 \n", "3960 2384 i-guttural 29 \n", "4335 6478 iii-guttural 135 \n", "11936 5268 i-nun 2010 \n", "20623 5268 i-nun 2010 \n", "20624 545 i-aleph 5307 \n", "21265 3352 i-waw, iii-guttural 205 \n", "21469 8127 ii-yod 583 \n", "21470 5539 i-guttural 548 \n", "22844 5268 i-nun 2010 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "3064 17527 0 wayq NaN 847 \n", "3960 22546 0 wayq DF 29 \n", "4335 24559 0 wayq DF_DL 135 \n", "11936 75563 0 wayq NaN 2010 \n", "20623 130599 0 wayq NaN 2010 \n", "20624 130604 0 wayq NaN 5307 \n", "21265 134354 0 wayq NaN 205 \n", "21469 135441 0 wayq NaN 583 \n", "21470 135446 0 wayq _DL 548 \n", "22844 142672 0 wayq NaN 2010 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 \\\n", "3064 9 >EC:L:X@H unknown Hebrew CLX[ absent sg \n", "3960 1 N.AXAL:M@H unknown Hebrew XLM[ absent pl \n", "4335 2 N.IP:T.:X@H unknown Hebrew PTX[ absent pl \n", "11936 37 >ET.:N@H unknown Hebrew NTN[ absent sg \n", "20623 37 >ET.:N@H unknown Hebrew NTN[ absent sg \n", "20624 45 >OM:R@H unknown Hebrew >MR[ absent sg \n", "21265 1 >OWCIJ<@H unknown Hebrew JC<[ absent sg \n", "21469 4 >@FIJM@H unknown Hebrew FJM[ absent sg \n", "21470 9 >E<:B.:R@H unknown Hebrew ET.:N@H unknown Hebrew NTN[ absent sg \n", "\n", " number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 \\\n", "3064 17528 verb > absent unknown unknown unknown p1 3421 \n", "3960 22547 verb N absent unknown unknown unknown p1 12851 \n", "4335 24560 verb N absent unknown unknown unknown p1 9178 \n", "11936 5954 verb > absent unknown unknown unknown p1 1046 \n", "20623 3149 verb > absent unknown unknown unknown p1 1046 \n", "20624 3154 verb > absent unknown unknown unknown p1 868 \n", "21265 6904 verb > absent unknown unknown unknown p1 12851 \n", "21469 7991 verb > absent unknown unknown unknown p1 6060 \n", "21470 7996 verb > absent unknown unknown unknown p1 3421 \n", "22844 1137 verb > absent unknown unknown unknown p1 1046 \n", "\n", " sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \\\n", "3064 verb NaN absent H= absent qal wayq False False \n", "3960 verb NaN absent H= absent qal wayq False False \n", "4335 verb NaN absent H= absent qal wayq False False \n", "11936 verb NaN absent H= absent qal wayq False False \n", "20623 verb NaN absent H= absent qal wayq False False \n", "20624 verb NaN absent H= absent qal wayq False False \n", "21265 verb NaN absent H= H hif wayq False False \n", "21469 verb NaN absent H= absent qal wayq False False \n", "21470 verb NaN absent H= absent qal wayq False False \n", "22844 verb NaN absent H= absent qal wayq False False \n", "\n", " Transposition \n", "3064 False \n", "3960 False \n", "4335 False \n", "11936 False \n", "20623 False \n", "20624 False \n", "21265 False \n", "21469 False \n", "21470 False \n", "22844 False " ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['language1']=='Hebrew') \n", " &\n", " (BHSallVerbalMorphology['vbe1']=='H=')\n", " & (BHSallVerbalMorphology['vt1']=='wayq')\n", " & (BHSallVerbalMorphology['ps1']=='p1') \n", " ].head(10)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEnding
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology['WayCohortEnding'] = ((BHSallVerbalMorphology['language1']=='Hebrew') \n", " &\n", " (BHSallVerbalMorphology['vbe1']=='H=')\n", " & (BHSallVerbalMorphology['vt1']=='wayq')\n", " & (BHSallVerbalMorphology['ps1']=='p1') \n", " )\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEnding
30643065Genesis32617528wordאֶשְׁלְחָה֙17528qal: send; ni: be sent; pi: let go; stretch ou...שׁלח7754iii-guttural847175270wayqNaN8479>EC:L:X@HunknownHebrewCLX[absentsg17528verb>absentunknownunknownunknownp13421verbNaNabsentH=absentqalwayqFalseFalseFalseTrue
39603961Genesis411122547wordנַּֽחַלְמָ֥ה22547qal: become strong; dream; hi: make strong;חלם2384i-guttural29225460wayqDF291N.AXAL:M@HunknownHebrewXLM[absentpl22547verbNabsentunknownunknownunknownp112851verbNaNabsentH=absentqalwayqFalseFalseFalseTrue
43354336Genesis432124560wordנִּפְתְּחָה֙24560qal: open; ni: be opened; pi: loose, free; hit...פתח I6478iii-guttural135245590wayqDF_DL1352N.IP:T.:X@HunknownHebrewPTX[absentpl24560verbNabsentunknownunknownunknownp19178verbNaNabsentH=absentqalwayqFalseFalseFalseTrue
1193611937Numbers81975564wordאֶתְּנָ֨ה75564qal: give, place; ni: be given, put; ho: be gi...נתן5268i-nun2010755630wayqNaN201037>ET.:N@HunknownHebrewNTN[absentsg5954verb>absentunknownunknownunknownp11046verbNaNabsentH=absentqalwayqFalseFalseFalseTrue
2062320624Judges69130600wordאֶתְּנָ֥ה130600qal: give, place; ni: be given, put; ho: be gi...נתן5268i-nun20101305990wayqNaN201037>ET.:N@HunknownHebrewNTN[absentsg3149verb>absentunknownunknownunknownp11046verbNaNabsentH=absentqalwayqFalseFalseFalseTrue
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "3064 3065 Genesis 32 6 17528 word אֶשְׁלְחָה֙ \n", "3960 3961 Genesis 41 11 22547 word נַּֽחַלְמָ֥ה \n", "4335 4336 Genesis 43 21 24560 word נִּפְתְּחָה֙ \n", "11936 11937 Numbers 8 19 75564 word אֶתְּנָ֨ה \n", "20623 20624 Judges 6 9 130600 word אֶתְּנָ֥ה \n", "\n", " bol_bhsa_word_order1 \\\n", "3064 17528 \n", "3960 22547 \n", "4335 24560 \n", "11936 75564 \n", "20623 130600 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "3064 qal: send; ni: be sent; pi: let go; stretch ou... שׁלח \n", "3960 qal: become strong; dream; hi: make strong; חלם \n", "4335 qal: open; ni: be opened; pi: loose, free; hit... פתח I \n", "11936 qal: give, place; ni: be given, put; ho: be gi... נתן \n", "20623 qal: give, place; ni: be given, put; ho: be gi... נתן \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "3064 7754 iii-guttural 847 17527 \n", "3960 2384 i-guttural 29 22546 \n", "4335 6478 iii-guttural 135 24559 \n", "11936 5268 i-nun 2010 75563 \n", "20623 5268 i-nun 2010 130599 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "3064 0 wayq NaN 847 9 \n", "3960 0 wayq DF 29 1 \n", "4335 0 wayq DF_DL 135 2 \n", "11936 0 wayq NaN 2010 37 \n", "20623 0 wayq NaN 2010 37 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 \\\n", "3064 >EC:L:X@H unknown Hebrew CLX[ absent sg 17528 verb \n", "3960 N.AXAL:M@H unknown Hebrew XLM[ absent pl 22547 verb \n", "4335 N.IP:T.:X@H unknown Hebrew PTX[ absent pl 24560 verb \n", "11936 >ET.:N@H unknown Hebrew NTN[ absent sg 5954 verb \n", "20623 >ET.:N@H unknown Hebrew NTN[ absent sg 3149 verb \n", "\n", " pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "3064 > absent unknown unknown unknown p1 3421 verb NaN \n", "3960 N absent unknown unknown unknown p1 12851 verb NaN \n", "4335 N absent unknown unknown unknown p1 9178 verb NaN \n", "11936 > absent unknown unknown unknown p1 1046 verb NaN \n", "20623 > absent unknown unknown unknown p1 1046 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \\\n", "3064 absent H= absent qal wayq False False \n", "3960 absent H= absent qal wayq False False \n", "4335 absent H= absent qal wayq False False \n", "11936 absent H= absent qal wayq False False \n", "20623 absent H= absent qal wayq False False \n", "\n", " Transposition WayCohortEnding \n", "3064 False True \n", "3960 False True \n", "4335 False True \n", "11936 False True \n", "20623 False True " ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['WayCohortEnding']==True)].head()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "R 98\n", "S1 98\n", "S2 98\n", "S3 98\n", "NODE1 98\n", "TYPE1 98\n", "TEXT1 98\n", "bol_bhsa_word_order1 98\n", "bol_dict_EN1 98\n", "bol_dict_HebArm1 98\n", "bol_dict_abc1 98\n", "bol_dict_vc1 98\n", "bol_lexeme_occurrences1 98\n", "bol_monad_num1 98\n", "bol_qere_presence1 98\n", "bol_vt1 98\n", "dagesh1 12\n", "freq_lex1 98\n", "freq_occ1 98\n", "g_word_noaccent1 98\n", "gn1 98\n", "language1 98\n", "lex1 98\n", "nme1 98\n", "nu1 98\n", "number1 98\n", "pdp1 98\n", "pfm1 98\n", "prs1 98\n", "prs_gn1 98\n", "prs_nu1 98\n", "prs_ps1 98\n", "ps1 98\n", "rank_occ1 98\n", "sp1 98\n", "st1 0\n", "uvf1 98\n", "vbe1 98\n", "vbs1 98\n", "vs1 98\n", "vt1 98\n", "paragogicNun 98\n", "emphaticImpv 98\n", "Transposition 98\n", "WayCohortEnding 98\n", "dtype: int64" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['WayCohortEnding']==True)].count()" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Adding Piel/Pual/Hitpael without DF as a data category" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['DL', nan, 'DF', 'DF_DL', '_DL', 'DF_DF', 'DL_DF', 'DL_DF_DF', 'DF_Mappiq', '_DL_DL', 'DF_DL_DF', 'DF_DF_Mappiq', 'DL_Mappiq', 'DF_DF_DF', 'DL_DF_Mappiq', 'DL_DF_DL', '_DF_DF']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.dagesh1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['qal', 'piel', 'hif', 'nif', 'pual', 'hit', 'hof', 'hsht', 'pasq', 'hotp', 'nit', 'poal', 'poel', 'htpo', 'peal', 'tif', 'etpa', 'pael', 'haf', 'htpe', 'htpa', 'peil', 'etpe', 'afel', 'shaf']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.vs1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['perf', 'ptca', 'wayq', 'impf', 'infc', 'impv', 'infa', 'ptcp']\n" ] } ], "source": [ "vbe=BHSallVerbalMorphology.vt1.unique().tolist()\n", "print(vbe)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEnding
3629636297Isaiah214218782wordבִּֽעֲתָ֑תְנִי218782ni: be terrified; pi: terrify;בעת1137ii-guttural162187810perfDL161B.I<:AT@T:NIJfHebrewB<T[absentsg6713verbabsentNJunknownsgp1p312851verbNaNabsentHabsentpielperfFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "36296 36297 Isaiah 21 4 218782 word בִּֽעֲתָ֑תְנִי \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 bol_dict_HebArm1 \\\n", "36296 218782 ni: be terrified; pi: terrify; בעת \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "36296 1137 ii-guttural 16 218781 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "36296 0 perf DL 16 1 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "36296 B.I<:AT@T:NIJ f Hebrew B]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[BGDKPT]\\.[:AEI][>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNS]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains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needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[H][I][T]:[BGDKPT]\\.[:AEI][>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNS]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " ( \n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains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n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEnding
6114861149Job3115343544wordיְכֻנֶ֗נּוּ343544ni: be firm, be established; pi: set up, const...כון3441ii-waw2163435430wayqNaN2161J:KUNEN.W.mHebrewKWN[absentsg7524verbJHWmsgp3p312851verbNaNNNaNabsentpielwayqFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "61148 61149 Job 31 15 343544 word יְכֻנֶ֗נּוּ 343544 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "61148 ni: be firm, be established; pi: set up, const... כון \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "61148 3441 ii-waw 216 343543 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "61148 0 wayq NaN 216 1 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "61148 J:KUNEN.W. m Hebrew KWN[ absent sg 7524 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 vbe1 \\\n", "61148 HW m sg p3 p3 12851 verb NaN N NaN \n", "\n", " vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "61148 absent piel wayq False False False \n", "\n", " WayCohortEnding \n", "61148 False " ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['g_word_noaccent1'].str.contains('[MJTN>]:[>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNS\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEnding
490491Genesis6162897wordתְּכַלֶ֣נָּה2897qal: come to an end, be completed, long for; p...כלה3494iii-hey20628970impfDL_DF2062T.:KALEN.@HmHebrewKLH[absentsg2897verbTHfsgp3p29178verbNaNNNaNabsentpielimpfFalseFalseFalseFalse
22112212Genesis261413258wordיְקַנְא֥וּ13258pi: be envious of; arouse jealousy; hi: make j...קנא6957iii-aleph34132580wayqNaN344J:QAN:>W.mHebrewQN>[absentpl13258verbJabsentunknownunknownunknownp36060verbNaNabsentWabsentpielwayqFalseFalseFalseFalse
22142215Genesis261513276wordיְמַלְא֖וּם13276qal: be full, fill (with), be filled (with); n...מלא4250iii-aleph261132760wayqNaN2922J:MAL:>W.MmHebrewML>[absentpl13276verbJMmplp3p39178verbNaNabsentWabsentpielwayqFalseFalseFalseFalse
29982999Genesis313917122wordתְּבַקְשֶׁ֑נָּה17122pi: seek; pu: be sought;בקשׁ1180regular225171210impfDL_DF2252T.:BAQ:CEN.@HmHebrewBQC[absentsg17122verbTHfsgp3p29178verbNaNNNaNabsentpielimpfFalseFalseFalseFalse
35213522Genesis371120379wordיְקַנְאוּ־20379pi: be envious of; arouse jealousy; hi: make j...קנא6957iii-aleph34203780wayqNaN344J:QAN:>W.mHebrewQN>[absentpl20379verbJabsentunknownunknownunknownp36060verbNaNabsentWabsentpielwayqFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "490 491 Genesis 6 16 2897 word תְּכַלֶ֣נָּה \n", "2211 2212 Genesis 26 14 13258 word יְקַנְא֥וּ \n", "2214 2215 Genesis 26 15 13276 word יְמַלְא֖וּם \n", "2998 2999 Genesis 31 39 17122 word תְּבַקְשֶׁ֑נָּה \n", "3521 3522 Genesis 37 11 20379 word יְקַנְאוּ־ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "490 2897 qal: come to an end, be completed, long for; p... \n", "2211 13258 pi: be envious of; arouse jealousy; hi: make j... \n", "2214 13276 qal: be full, fill (with), be filled (with); n... \n", "2998 17122 pi: seek; pu: be sought; \n", "3521 20379 pi: be envious of; arouse jealousy; hi: make j... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "490 כלה 3494 iii-hey 206 \n", "2211 קנא 6957 iii-aleph 34 \n", "2214 מלא 4250 iii-aleph 261 \n", "2998 בקשׁ 1180 regular 225 \n", "3521 קנא 6957 iii-aleph 34 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "490 2897 0 impf DL_DF 206 \n", "2211 13258 0 wayq NaN 34 \n", "2214 13276 0 wayq NaN 292 \n", "2998 17121 0 impf DL_DF 225 \n", "3521 20378 0 wayq NaN 34 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "490 2 T.:KALEN.@H m Hebrew KLH[ absent sg 2897 \n", "2211 4 J:QAN:>W. m Hebrew QN>[ absent pl 13258 \n", "2214 2 J:MAL:>W.M m Hebrew ML>[ absent pl 13276 \n", "2998 2 T.:BAQ:CEN.@H m Hebrew BQC[ absent sg 17122 \n", "3521 4 J:QAN:>W. m Hebrew QN>[ absent pl 20379 \n", "\n", " pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "490 verb T H f sg p3 p2 9178 verb NaN \n", "2211 verb J absent unknown unknown unknown p3 6060 verb NaN \n", "2214 verb J M m pl p3 p3 9178 verb NaN \n", "2998 verb T H f sg p3 p2 9178 verb NaN \n", "3521 verb J absent unknown unknown unknown p3 6060 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \\\n", "490 N NaN absent piel impf False False \n", "2211 absent W absent piel wayq False False \n", "2214 absent W absent piel wayq False False \n", "2998 N NaN absent piel impf False False \n", "3521 absent W absent piel wayq False False \n", "\n", " Transposition WayCohortEnding \n", "490 False False \n", "2211 False False \n", "2214 False False \n", "2998 False False \n", "3521 False False " ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[\n", " (\n", " (BHSallVerbalMorphology['language1']=='Hebrew') \n", " &\n", " (\n", " (BHSallVerbalMorphology['vs1']=='piel')\n", " |(BHSallVerbalMorphology['vs1']=='pual')\n", " )\n", " & (\n", " (BHSallVerbalMorphology['vt1']=='perf')\n", " |(BHSallVerbalMorphology['vt1'].str.contains('inf'))\n", " |(BHSallVerbalMorphology['vt1'].str.contains('imp'))\n", " \n", " )\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-waw.*')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-yod.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*geminate.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", "\n", " & (~BHSallVerbalMorphology['pfm1'].astype(str).str.contains('[MJTN>]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[BGDKPT]\\.[:AEI][>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNS]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains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n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEnding
64196420Exodus141336484wordהִֽתְיַצְב֗וּ36484hit: take one's stand, position, stand (firm);...יצב3208i-waw48364830impvNaN489HIT:JAY:BW.mHebrewJYB[absentpl7721verbNaNabsentunknownunknownunknownp23421verbNaNabsentWHThitimpvFalseFalseFalseFalse
1134711348Numbers11869802wordיִּתְיַֽלְד֥וּ69802qal: bear, bring forth; beget; qal pass: bear,...ילד3096i-waw492698010wayqDF4921J.IT:JAL:DW.mHebrewJLD[absentpl192verbJabsentunknownunknownunknownp312851verbNaNabsentWHThitwayqFalseFalseFalseFalse
3891338914Isaiah522230323wordהִתְנַעֲרִ֧י230323qal: shake, shake off; ni: be shaken off, shak...נער I5149i-nun, ii-guttural112303220impvNaN111HIT:NA<:ARIJfHebrewN<R[absentsg18254verbNaNabsentunknownunknownunknownp212851verbNaNabsentJHThitimpvFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "6419 6420 Exodus 14 13 36484 word הִֽתְיַצְב֗וּ \n", "11347 11348 Numbers 1 18 69802 word יִּתְיַֽלְד֥וּ \n", "38913 38914 Isaiah 52 2 230323 word הִתְנַעֲרִ֧י \n", "\n", " bol_bhsa_word_order1 \\\n", "6419 36484 \n", "11347 69802 \n", "38913 230323 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "6419 hit: take one's stand, position, stand (firm);... יצב \n", "11347 qal: bear, bring forth; beget; qal pass: bear,... ילד \n", "38913 qal: shake, shake off; ni: be shaken off, shak... נער I \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "6419 3208 i-waw 48 \n", "11347 3096 i-waw 492 \n", "38913 5149 i-nun, ii-guttural 11 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "6419 36483 0 impv NaN 48 \n", "11347 69801 0 wayq DF 492 \n", "38913 230322 0 impv NaN 11 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "6419 9 HIT:JAY:BW. m Hebrew JYB[ absent pl 7721 \n", "11347 1 J.IT:JAL:DW. m Hebrew JLD[ absent pl 192 \n", "38913 1 HIT:NA<:ARIJ f Hebrew N]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[H][I][T]:[BGDKPT]\\.[:AEI][>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNS]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " ( \n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains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n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengthening
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False " ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology['PielPualHit_wo_DF_compLengthening'] = ((BHSallVerbalMorphology['language1']=='Hebrew') \n", " &\n", " (\n", " (\n", " (\n", " (BHSallVerbalMorphology['vs1']=='piel')\n", " |(BHSallVerbalMorphology['vs1']=='pual')\n", " )\n", " & (\n", " (BHSallVerbalMorphology['vt1']=='perf')\n", " |(BHSallVerbalMorphology['vt1'].str.contains('inf'))\n", " |(BHSallVerbalMorphology['vt1'].str.contains('imp'))\n", " \n", " )\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-waw.*')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-yod.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*geminate.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", "\n", " & (~BHSallVerbalMorphology['pfm1'].astype(str).str.contains('[MJTN>]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[BGDKPT]\\.[:AEI][>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNS]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains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needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " (\n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[H][I][T]:[BGDKPT]\\.[:AEI][>BGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNSHWZXVJLMNSBGDHWZXVJKLMNS]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " &\n", " ( \n", " (BHSallVerbalMorphology['g_word_noaccent1'].str.contains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n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengthening
490491Genesis6162897wordתְּכַלֶ֣נָּה2897qal: come to an end, be completed, long for; p...כלה3494iii-hey20628970impfDL_DF2062T.:KALEN.@HmHebrewKLH[absentsg2897verbTHfsgp3p29178verbNaNNNaNabsentpielimpfFalseFalseFalseFalseTrue
22112212Genesis261413258wordיְקַנְא֥וּ13258pi: be envious of; arouse jealousy; hi: make j...קנא6957iii-aleph34132580wayqNaN344J:QAN:>W.mHebrewQN>[absentpl13258verbJabsentunknownunknownunknownp36060verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
22142215Genesis261513276wordיְמַלְא֖וּם13276qal: be full, fill (with), be filled (with); n...מלא4250iii-aleph261132760wayqNaN2922J:MAL:>W.MmHebrewML>[absentpl13276verbJMmplp3p39178verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
29982999Genesis313917122wordתְּבַקְשֶׁ֑נָּה17122pi: seek; pu: be sought;בקשׁ1180regular225171210impfDL_DF2252T.:BAQ:CEN.@HmHebrewBQC[absentsg17122verbTHfsgp3p29178verbNaNNNaNabsentpielimpfFalseFalseFalseFalseTrue
35213522Genesis371120379wordיְקַנְאוּ־20379pi: be envious of; arouse jealousy; hi: make j...קנא6957iii-aleph34203780wayqNaN344J:QAN:>W.mHebrewQN>[absentpl20379verbJabsentunknownunknownunknownp36060verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "490 491 Genesis 6 16 2897 word תְּכַלֶ֣נָּה \n", "2211 2212 Genesis 26 14 13258 word יְקַנְא֥וּ \n", "2214 2215 Genesis 26 15 13276 word יְמַלְא֖וּם \n", "2998 2999 Genesis 31 39 17122 word תְּבַקְשֶׁ֑נָּה \n", "3521 3522 Genesis 37 11 20379 word יְקַנְאוּ־ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "490 2897 qal: come to an end, be completed, long for; p... \n", "2211 13258 pi: be envious of; arouse jealousy; hi: make j... \n", "2214 13276 qal: be full, fill (with), be filled (with); n... \n", "2998 17122 pi: seek; pu: be sought; \n", "3521 20379 pi: be envious of; arouse jealousy; hi: make j... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "490 כלה 3494 iii-hey 206 \n", "2211 קנא 6957 iii-aleph 34 \n", "2214 מלא 4250 iii-aleph 261 \n", "2998 בקשׁ 1180 regular 225 \n", "3521 קנא 6957 iii-aleph 34 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "490 2897 0 impf DL_DF 206 \n", "2211 13258 0 wayq NaN 34 \n", "2214 13276 0 wayq NaN 292 \n", "2998 17121 0 impf DL_DF 225 \n", "3521 20378 0 wayq NaN 34 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "490 2 T.:KALEN.@H m Hebrew KLH[ absent sg 2897 \n", "2211 4 J:QAN:>W. m Hebrew QN>[ absent pl 13258 \n", "2214 2 J:MAL:>W.M m Hebrew ML>[ absent pl 13276 \n", "2998 2 T.:BAQ:CEN.@H m Hebrew BQC[ absent sg 17122 \n", "3521 4 J:QAN:>W. m Hebrew QN>[ absent pl 20379 \n", "\n", " pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "490 verb T H f sg p3 p2 9178 verb NaN \n", "2211 verb J absent unknown unknown unknown p3 6060 verb NaN \n", "2214 verb J M m pl p3 p3 9178 verb NaN \n", "2998 verb T H f sg p3 p2 9178 verb NaN \n", "3521 verb J absent unknown unknown unknown p3 6060 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \\\n", "490 N NaN absent piel impf False False \n", "2211 absent W absent piel wayq False False \n", "2214 absent W absent piel wayq False False \n", "2998 N NaN absent piel impf False False \n", "3521 absent W absent piel wayq False False \n", "\n", " Transposition WayCohortEnding PielPualHit_wo_DF_compLengthening \n", "490 False False True \n", "2211 False False True \n", "2214 False False True \n", "2998 False False True \n", "3521 False False True " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['PielPualHit_wo_DF_compLengthening']==True)].head()" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengthening
22112212Genesis261413258wordיְקַנְא֥וּ13258pi: be envious of; arouse jealousy; hi: make j...קנא6957iii-aleph34132580wayqNaN344J:QAN:>W.mHebrewQN>[absentpl13258verbJabsentunknownunknownunknownp36060verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
22142215Genesis261513276wordיְמַלְא֖וּם13276qal: be full, fill (with), be filled (with); n...מלא4250iii-aleph261132760wayqNaN2922J:MAL:>W.MmHebrewML>[absentpl13276verbJMmplp3p39178verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
35213522Genesis371120379wordיְקַנְאוּ־20379pi: be envious of; arouse jealousy; hi: make j...קנא6957iii-aleph34203780wayqNaN344J:QAN:>W.mHebrewQN>[absentpl20379verbJabsentunknownunknownunknownp36060verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
41904191Genesis422523851wordיְמַלְא֣וּ23851qal: be full, fill (with), be filled (with); n...מלא4250iii-aleph261238500wayqNaN29212J:MAL:>W.mHebrewML>[absentpl23851verbJabsentunknownunknownunknownp32761verbNaNabsentWabsentpielwayqFalseFalseFalseFalseTrue
64726473Exodus142736807wordיְנַעֵ֧ר36807qal: shake, shake off; ni: be shaken off, shak...נער I5149i-nun, ii-guttural11368060wayqNaN112J:NA<;RmHebrewN<R[absentsg8044verbJabsentunknownunknownunknownp39178verbNaNabsentNaNabsentpielwayqFalseFalseFalseFalseTrue
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "2211 2212 Genesis 26 14 13258 word יְקַנְא֥וּ 13258 \n", "2214 2215 Genesis 26 15 13276 word יְמַלְא֖וּם 13276 \n", "3521 3522 Genesis 37 11 20379 word יְקַנְאוּ־ 20379 \n", "4190 4191 Genesis 42 25 23851 word יְמַלְא֣וּ 23851 \n", "6472 6473 Exodus 14 27 36807 word יְנַעֵ֧ר 36807 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "2211 pi: be envious of; arouse jealousy; hi: make j... קנא \n", "2214 qal: be full, fill (with), be filled (with); n... מלא \n", "3521 pi: be envious of; arouse jealousy; hi: make j... קנא \n", "4190 qal: be full, fill (with), be filled (with); n... מלא \n", "6472 qal: shake, shake off; ni: be shaken off, shak... נער I \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "2211 6957 iii-aleph 34 \n", "2214 4250 iii-aleph 261 \n", "3521 6957 iii-aleph 34 \n", "4190 4250 iii-aleph 261 \n", "6472 5149 i-nun, ii-guttural 11 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "2211 13258 0 wayq NaN 34 \n", "2214 13276 0 wayq NaN 292 \n", "3521 20378 0 wayq NaN 34 \n", "4190 23850 0 wayq NaN 292 \n", "6472 36806 0 wayq NaN 11 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "2211 4 J:QAN:>W. m Hebrew QN>[ absent pl 13258 \n", "2214 2 J:MAL:>W.M m Hebrew ML>[ absent pl 13276 \n", "3521 4 J:QAN:>W. m Hebrew QN>[ absent pl 20379 \n", "4190 12 J:MAL:>W. m Hebrew ML>[ absent pl 23851 \n", "6472 2 J:NA<;R m Hebrew N\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengthening
3629636297Isaiah214218782wordבִּֽעֲתָ֑תְנִי218782ni: be terrified; pi: terrify;בעת1137ii-guttural162187810perfDL161B.I<:AT@T:NIJfHebrewB<T[absentsg6713verbabsentNJunknownsgp1p312851verbNaNabsentHabsentpielperfFalseFalseFalseFalseTrue
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "36296 36297 Isaiah 21 4 218782 word בִּֽעֲתָ֑תְנִי \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 bol_dict_HebArm1 \\\n", "36296 218782 ni: be terrified; pi: terrify; בעת \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "36296 1137 ii-guttural 16 218781 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "36296 0 perf DL 16 1 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "36296 B.I<:AT@T:NIJ f Hebrew B\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengthening
5502355024Psalms3811316708wordסְ֭חַרְחַר316708qal: through, wander around; pi: palpitate hea...סחר5351ii-guttural213167070perfNaN211S:XAR:XARmHebrewSXR[absentsg6059verbabsentabsentunknownunknownunknownp312851verbNaNabsentNaNabsentpielperfFalseFalseFalseFalseFalse
6534165342Lamentations120363904wordחֳמַרְמָ֔רוּ363904qal: cover; foam; pi: ferment;חמר I2458i-guttural53639030perfNaN52X:@MAR:M@RW.unknownHebrewXMR[absentpl396verbabsentabsentunknownunknownunknownp39178verbNaNabsentWabsentpielperfFalseFalseFalseFalseFalse
6540965410Lamentations211364185wordחֳמַרְמְר֣וּ364185qal: cover; foam; pi: ferment;חמר I2458i-guttural53641840perfNaN52X:@MAR:M:RW.unknownHebrewXMR[absentpl677verbabsentabsentunknownunknownunknownp39178verbNaNabsentWabsentpielperfFalseFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "55023 55024 Psalms 38 11 316708 word סְ֭חַרְחַר \n", "65341 65342 Lamentations 1 20 363904 word חֳמַרְמָ֔רוּ \n", "65409 65410 Lamentations 2 11 364185 word חֳמַרְמְר֣וּ \n", "\n", " bol_bhsa_word_order1 \\\n", "55023 316708 \n", "65341 363904 \n", "65409 364185 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "55023 qal: through, wander around; pi: palpitate hea... סחר \n", "65341 qal: cover; foam; pi: ferment; חמר I \n", "65409 qal: cover; foam; pi: ferment; חמר I \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "55023 5351 ii-guttural 21 316707 \n", "65341 2458 i-guttural 5 363903 \n", "65409 2458 i-guttural 5 364184 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "55023 0 perf NaN 21 1 \n", "65341 0 perf NaN 5 2 \n", "65409 0 perf NaN 5 2 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 \\\n", "55023 S:XAR:XAR m Hebrew SXR[ absent sg 6059 verb \n", "65341 X:@MAR:M@RW. unknown Hebrew XMR[ absent pl 396 verb \n", "65409 X:@MAR:M:RW. unknown Hebrew XMR[ absent pl 677 verb \n", "\n", " pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "55023 absent absent unknown unknown unknown p3 12851 verb NaN \n", "65341 absent absent unknown unknown unknown p3 9178 verb NaN \n", "65409 absent absent unknown unknown unknown p3 9178 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \\\n", "55023 absent NaN absent piel perf False False \n", "65341 absent W absent piel perf False False \n", "65409 absent W absent piel perf False False \n", "\n", " Transposition WayCohortEnding PielPualHit_wo_DF_compLengthening \n", "55023 False False False \n", "65341 False False False \n", "65409 False False False " ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# code working for perfect\n", "BHSallVerbalMorphology[\n", " (BHSallVerbalMorphology['vs1']=='piel')\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-waw.*')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-yod.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*geminate.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", "\n", " & (~BHSallVerbalMorphology['pfm1'].astype(str).str.contains('[MJTN>]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " & (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[>BGDHWZXVJKLMNS\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengthening
13981399Genesis19168774wordיִּתְמַהְמָ֓הּ׀8774hit: hesitate, delay, tarry, linger;מָהַהּ3971ii-guttural987740wayqDF_Mappiq92J.IT:MAH:M@H.mHebrewMHH[absentsg8774verbJabsentunknownunknownunknownp39178verbNaNabsentNaNHThitwayqFalseFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "1398 1399 Genesis 19 16 8774 word יִּתְמַהְמָ֓הּ׀ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "1398 8774 hit: hesitate, delay, tarry, linger; \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "1398 מָהַהּ 3971 ii-guttural 9 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "1398 8774 0 wayq DF_Mappiq 9 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 \\\n", "1398 2 J.IT:MAH:M@H. m Hebrew MHH[ absent sg 8774 \n", "\n", " pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "1398 verb J absent unknown unknown unknown p3 9178 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "1398 absent NaN HT hit wayq False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \n", "1398 False False " ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[\n", " # Catching Guttural without compensatory lengthening (excluding X) in ptc\n", " (\n", " (BHSallVerbalMorphology['vs1']=='hit')\n", " & (\n", " (BHSallVerbalMorphology['vt1'].str.contains('way'))\n", " )\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-waw.*')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-yod.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*geminate.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", "\n", " & (BHSallVerbalMorphology['pfm1'].astype(str).str.contains('[JT>N]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " & (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('[JT>N][\\.][I][T][:][>BGDHWZXVJKLMNSXH\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology['PielPualHit_w_DoubleDoubling'] = ((BHSallVerbalMorphology['language1']=='Hebrew') \n", " &\n", " (\n", " (BHSallVerbalMorphology['vs1']=='hit')\n", " & (\n", " (BHSallVerbalMorphology['vt1'].str.contains('way'))\n", " )\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-waw.*')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*ii-yod.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", " & (~BHSallVerbalMorphology['bol_dict_vc1'].astype(str).str.contains('.*geminate.*')) # I needed to put 'astype(str)' there because there were NaN values in the data \n", "\n", " & (BHSallVerbalMorphology['pfm1'].astype(str).str.contains('[JT>N]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " & (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('[JT>N][\\.][I][T][:][>BGDHWZXVJKLMNSXH]')) # I needed to put 'astype(str)' there because there were NaN values in the data\n", " \n", " & (BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^[>BGDHWZXVJKLMNS\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
13981399Genesis19168774wordיִּתְמַהְמָ֓הּ׀8774hit: hesitate, delay, tarry, linger;מָהַהּ3971ii-guttural987740wayqDF_Mappiq92J.IT:MAH:M@H.mHebrewMHH[absentsg8774verbJabsentunknownunknownunknownp39178verbNaNabsentNaNHThitwayqFalseFalseFalseFalseFalseTrue
5502355024Psalms3811316708wordסְ֭חַרְחַר316708qal: through, wander around; pi: palpitate hea...סחר5351ii-guttural213167070perfNaN211S:XAR:XARmHebrewSXR[absentsg6059verbabsentabsentunknownunknownunknownp312851verbNaNabsentNaNabsentpielperfFalseFalseFalseFalseFalseTrue
6534165342Lamentations120363904wordחֳמַרְמָ֔רוּ363904qal: cover; foam; pi: ferment;חמר I2458i-guttural53639030perfNaN52X:@MAR:M@RW.unknownHebrewXMR[absentpl396verbabsentabsentunknownunknownunknownp39178verbNaNabsentWabsentpielperfFalseFalseFalseFalseFalseTrue
6540965410Lamentations211364185wordחֳמַרְמְר֣וּ364185qal: cover; foam; pi: ferment;חמר I2458i-guttural53641840perfNaN52X:@MAR:M:RW.unknownHebrewXMR[absentpl677verbabsentabsentunknownunknownunknownp39178verbNaNabsentWabsentpielperfFalseFalseFalseFalseFalseTrue
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "1398 1399 Genesis 19 16 8774 word יִּתְמַהְמָ֓הּ׀ \n", "55023 55024 Psalms 38 11 316708 word סְ֭חַרְחַר \n", "65341 65342 Lamentations 1 20 363904 word חֳמַרְמָ֔רוּ \n", "65409 65410 Lamentations 2 11 364185 word חֳמַרְמְר֣וּ \n", "\n", " bol_bhsa_word_order1 \\\n", "1398 8774 \n", "55023 316708 \n", "65341 363904 \n", "65409 364185 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "1398 hit: hesitate, delay, tarry, linger; מָהַהּ \n", "55023 qal: through, wander around; pi: palpitate hea... סחר \n", "65341 qal: cover; foam; pi: ferment; חמר I \n", "65409 qal: cover; foam; pi: ferment; חמר I \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 bol_monad_num1 \\\n", "1398 3971 ii-guttural 9 8774 \n", "55023 5351 ii-guttural 21 316707 \n", "65341 2458 i-guttural 5 363903 \n", "65409 2458 i-guttural 5 364184 \n", "\n", " bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "1398 0 wayq DF_Mappiq 9 2 \n", "55023 0 perf NaN 21 1 \n", "65341 0 perf NaN 5 2 \n", "65409 0 perf NaN 5 2 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 \\\n", "1398 J.IT:MAH:M@H. m Hebrew MHH[ absent sg 8774 verb \n", "55023 S:XAR:XAR m Hebrew SXR[ absent sg 6059 verb \n", "65341 X:@MAR:M@RW. unknown Hebrew XMR[ absent pl 396 verb \n", "65409 X:@MAR:M:RW. unknown Hebrew XMR[ absent pl 677 verb \n", "\n", " pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 \\\n", "1398 J absent unknown unknown unknown p3 9178 verb NaN \n", "55023 absent absent unknown unknown unknown p3 12851 verb NaN \n", "65341 absent absent unknown unknown unknown p3 9178 verb NaN \n", "65409 absent absent unknown unknown unknown p3 9178 verb NaN \n", "\n", " uvf1 vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv \\\n", "1398 absent NaN HT hit wayq False False \n", "55023 absent NaN absent piel perf False False \n", "65341 absent W absent piel perf False False \n", "65409 absent W absent piel perf False False \n", "\n", " Transposition WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "1398 False False False \n", "55023 False False False \n", "65341 False False False \n", "65409 False False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "1398 True \n", "55023 True \n", "65341 True \n", "65409 True " ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology[(BHSallVerbalMorphology['PielPualHit_w_DoubleDoubling']==True)].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exporting Enriched Data Set of Verbal Morphology" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphology.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_morphology_all-verbs_with-additional-data-features_v20240220.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Selecting Qualifier Morphology: OTST551 & OTST552 & OTST625 morphology (only verbs that were part of the vocabulary)\n", "- excluding 4 root verbs\n", "- excluding Aramaic words\n", "- excluding specific difficulties" ] }, { "cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphology=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_morphology_all-verbs_with-additional-data-features_v20240220.xlsx')" ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
001Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
112Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
223Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
334Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
445Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 0 1 Genesis 1 1 3 word בָּרָ֣א \n", "1 1 2 Genesis 1 2 15 word הָיְתָ֥ה \n", "2 2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת \n", "3 3 4 Genesis 1 3 33 word יֹּ֥אמֶר \n", "4 4 5 Genesis 1 3 35 word יְהִ֣י \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "0 3 qal: create; ni: be created; \n", "1 15 qal: be, happen, become, occur; ni: be realize... \n", "2 27 qal: shake; pi: hover; \n", "3 33 qal: say, think; ni: be said, be called; hi: d... \n", "4 35 qal: be, happen, become, occur; ni: be realize... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "0 ברא I 1188 ii-guttural, iii-aleph \n", "1 היה 1864 i-guttural, iii-hey \n", "2 רחף 7238 i-guttural, ii-guttural \n", "3 אמר I 545 i-aleph \n", "4 היה 1864 i-guttural, iii-hey \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "0 48 3 0 perf \n", "1 3561 15 0 perf \n", "2 3 27 0 ptca \n", "3 5307 33 0 wayq \n", "4 3561 35 0 juss \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 \\\n", "0 DL 48 15 B.@R@> m Hebrew BR>[ absent \n", "1 NaN 3561 209 H@J:T@H f Hebrew HJH[ absent \n", "2 NaN 3 1 M:RAXEPET f Hebrew RXP[ T \n", "3 DF 5307 2160 J.O>MER m Hebrew >MR[ absent \n", "4 NaN 3561 866 J:HIJ m Hebrew HJH[ absent \n", "\n", " nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 \\\n", "0 sg 3 verb absent absent unknown unknown unknown p3 \n", "1 sg 15 verb absent absent unknown unknown unknown p3 \n", "2 sg 27 verb M absent unknown unknown unknown unknown \n", "3 sg 33 verb J absent unknown unknown unknown p3 \n", "4 sg 35 verb J absent unknown unknown unknown p3 \n", "\n", " rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "0 2341 verb NaN absent NaN absent qal perf False \n", "1 204 verb NaN absent H absent qal perf False \n", "2 12851 verb a absent NaN absent piel ptca False \n", "3 18 verb NaN absent NaN absent qal wayq False \n", "4 38 verb NaN absent NaN absent qal impf False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "0 False False False \n", "1 False False False \n", "2 False False False \n", "3 False False False \n", "4 False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False " ] }, "execution_count": 140, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.set_option('display.max_rows', None)\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 141, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphology = BHSallVerbalMorphology.drop(\"Unnamed: 0\", axis='columns')\n", "BHSallVerbalMorphology.head()" ] }, { "cell_type": "code", "execution_count": 142, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 142, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphology[\n", " (BHSallVerbalMorphology['bol_dict_vc1']!='4 root verb') \n", " & (BHSallVerbalMorphology['language1']=='Hebrew')\n", " & (~BHSallVerbalMorphology['g_word_noaccent1'].str.contains('^\\*') # excluding ketiv qere matters\n", " & (\n", " (BHSallVerbalMorphology['vs1']=='qal')\n", " | (BHSallVerbalMorphology['vs1']=='nif')\n", " | (BHSallVerbalMorphology['vs1']=='piel')\n", " | (BHSallVerbalMorphology['vs1']=='pual')\n", " | (BHSallVerbalMorphology['vs1']=='hit')\n", " | (BHSallVerbalMorphology['vs1']=='hif')\n", " | (BHSallVerbalMorphology['vs1']=='hof')\n", " )\n", " )]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 72025 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 72025 non-null int64 \n", " 1 S1 72025 non-null object\n", " 2 S2 72025 non-null int64 \n", " 3 S3 72025 non-null int64 \n", " 4 NODE1 72025 non-null int64 \n", " 5 TYPE1 72025 non-null object\n", " 6 TEXT1 72025 non-null object\n", " 7 bol_bhsa_word_order1 72025 non-null int64 \n", " 8 bol_dict_EN1 72025 non-null object\n", " 9 bol_dict_HebArm1 72025 non-null object\n", " 10 bol_dict_abc1 72025 non-null int64 \n", " 11 bol_dict_vc1 72025 non-null object\n", " 12 bol_lexeme_occurrences1 72025 non-null int64 \n", " 13 bol_monad_num1 72025 non-null int64 \n", " 14 bol_qere_presence1 72025 non-null int64 \n", " 15 bol_vt1 72025 non-null object\n", " 16 dagesh1 25284 non-null object\n", " 17 freq_lex1 72025 non-null int64 \n", " 18 freq_occ1 72025 non-null int64 \n", " 19 g_word_noaccent1 72025 non-null object\n", " 20 gn1 72025 non-null object\n", " 21 language1 72025 non-null object\n", " 22 lex1 72025 non-null object\n", " 23 nme1 61870 non-null object\n", " 24 nu1 72025 non-null object\n", " 25 number1 72025 non-null int64 \n", " 26 pdp1 72025 non-null object\n", " 27 pfm1 60781 non-null object\n", " 28 prs1 72025 non-null object\n", " 29 prs_gn1 72025 non-null object\n", " 30 prs_nu1 72025 non-null object\n", " 31 prs_ps1 72025 non-null object\n", " 32 ps1 72025 non-null object\n", " 33 rank_occ1 72025 non-null int64 \n", " 34 sp1 72025 non-null object\n", " 35 st1 16658 non-null object\n", " 36 uvf1 72025 non-null object\n", " 37 vbe1 22506 non-null object\n", " 38 vbs1 72025 non-null object\n", " 39 vs1 72025 non-null object\n", " 40 vt1 72025 non-null object\n", " 41 paragogicNun 72025 non-null bool \n", " 42 emphaticImpv 72025 non-null bool \n", " 43 Transposition 72025 non-null bool \n", " 44 WayCohortEnding 72025 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 72025 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 72025 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.5+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Excluding 1stP Way forms with H" ] }, { "cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[False, True]\n" ] } ], "source": [ "vt=BHSallVerbalMorphologyOTST551_552_625.WayCohortEnding.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 145, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " (~BHSallVerbalMorphologyOTST551_552_625['WayCohortEnding']==True)\n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [R, S1, S2, S3, NODE1, TYPE1, TEXT1, bol_bhsa_word_order1, bol_dict_EN1, bol_dict_HebArm1, bol_dict_abc1, bol_dict_vc1, bol_lexeme_occurrences1, bol_monad_num1, bol_qere_presence1, bol_vt1, dagesh1, freq_lex1, freq_occ1, g_word_noaccent1, gn1, language1, lex1, nme1, nu1, number1, pdp1, pfm1, prs1, prs_gn1, prs_nu1, prs_ps1, ps1, rank_occ1, sp1, st1, uvf1, vbe1, vbs1, vs1, vt1, paragogicNun, emphaticImpv, Transposition, WayCohortEnding, PielPualHit_wo_DF_compLengthening, PielPualHit_w_DoubleDoubling]\n", "Index: []" ] }, "execution_count": 146, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625[(BHSallVerbalMorphologyOTST551_552_625['WayCohortEnding']==True)].head()" ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71928 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71928 non-null int64 \n", " 1 S1 71928 non-null object\n", " 2 S2 71928 non-null int64 \n", " 3 S3 71928 non-null int64 \n", " 4 NODE1 71928 non-null int64 \n", " 5 TYPE1 71928 non-null object\n", " 6 TEXT1 71928 non-null object\n", " 7 bol_bhsa_word_order1 71928 non-null int64 \n", " 8 bol_dict_EN1 71928 non-null object\n", " 9 bol_dict_HebArm1 71928 non-null object\n", " 10 bol_dict_abc1 71928 non-null int64 \n", " 11 bol_dict_vc1 71928 non-null object\n", " 12 bol_lexeme_occurrences1 71928 non-null int64 \n", " 13 bol_monad_num1 71928 non-null int64 \n", " 14 bol_qere_presence1 71928 non-null int64 \n", " 15 bol_vt1 71928 non-null object\n", " 16 dagesh1 25272 non-null object\n", " 17 freq_lex1 71928 non-null int64 \n", " 18 freq_occ1 71928 non-null int64 \n", " 19 g_word_noaccent1 71928 non-null object\n", " 20 gn1 71928 non-null object\n", " 21 language1 71928 non-null object\n", " 22 lex1 71928 non-null object\n", " 23 nme1 61773 non-null object\n", " 24 nu1 71928 non-null object\n", " 25 number1 71928 non-null int64 \n", " 26 pdp1 71928 non-null object\n", " 27 pfm1 60684 non-null object\n", " 28 prs1 71928 non-null object\n", " 29 prs_gn1 71928 non-null object\n", " 30 prs_nu1 71928 non-null object\n", " 31 prs_ps1 71928 non-null object\n", " 32 ps1 71928 non-null object\n", " 33 rank_occ1 71928 non-null int64 \n", " 34 sp1 71928 non-null object\n", " 35 st1 16658 non-null object\n", " 36 uvf1 71928 non-null object\n", " 37 vbe1 22409 non-null object\n", " 38 vbs1 71928 non-null object\n", " 39 vs1 71928 non-null object\n", " 40 vt1 71928 non-null object\n", " 41 paragogicNun 71928 non-null bool \n", " 42 emphaticImpv 71928 non-null bool \n", " 43 Transposition 71928 non-null bool \n", " 44 WayCohortEnding 71928 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71928 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71928 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.5+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Excluding Emphatic Imperatives" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[False, True]\n" ] } ], "source": [ "vt=BHSallVerbalMorphologyOTST551_552_625.emphaticImpv.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 149, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " (~BHSallVerbalMorphologyOTST551_552_625['emphaticImpv']==True)\n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 150, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [R, S1, S2, S3, NODE1, TYPE1, TEXT1, bol_bhsa_word_order1, bol_dict_EN1, bol_dict_HebArm1, bol_dict_abc1, bol_dict_vc1, bol_lexeme_occurrences1, bol_monad_num1, bol_qere_presence1, bol_vt1, dagesh1, freq_lex1, freq_occ1, g_word_noaccent1, gn1, language1, lex1, nme1, nu1, number1, pdp1, pfm1, prs1, prs_gn1, prs_nu1, prs_ps1, ps1, rank_occ1, sp1, st1, uvf1, vbe1, vbs1, vs1, vt1, paragogicNun, emphaticImpv, Transposition, WayCohortEnding, PielPualHit_wo_DF_compLengthening, PielPualHit_w_DoubleDoubling]\n", "Index: []" ] }, "execution_count": 150, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625[(BHSallVerbalMorphologyOTST551_552_625['emphaticImpv']==True)].head()" ] }, { "cell_type": "code", "execution_count": 151, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71629 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71629 non-null int64 \n", " 1 S1 71629 non-null object\n", " 2 S2 71629 non-null int64 \n", " 3 S3 71629 non-null int64 \n", " 4 NODE1 71629 non-null int64 \n", " 5 TYPE1 71629 non-null object\n", " 6 TEXT1 71629 non-null object\n", " 7 bol_bhsa_word_order1 71629 non-null int64 \n", " 8 bol_dict_EN1 71629 non-null object\n", " 9 bol_dict_HebArm1 71629 non-null object\n", " 10 bol_dict_abc1 71629 non-null int64 \n", " 11 bol_dict_vc1 71629 non-null object\n", " 12 bol_lexeme_occurrences1 71629 non-null int64 \n", " 13 bol_monad_num1 71629 non-null int64 \n", " 14 bol_qere_presence1 71629 non-null int64 \n", " 15 bol_vt1 71629 non-null object\n", " 16 dagesh1 25237 non-null object\n", " 17 freq_lex1 71629 non-null int64 \n", " 18 freq_occ1 71629 non-null int64 \n", " 19 g_word_noaccent1 71629 non-null object\n", " 20 gn1 71629 non-null object\n", " 21 language1 71629 non-null object\n", " 22 lex1 71629 non-null object\n", " 23 nme1 61474 non-null object\n", " 24 nu1 71629 non-null object\n", " 25 number1 71629 non-null int64 \n", " 26 pdp1 71629 non-null object\n", " 27 pfm1 60679 non-null object\n", " 28 prs1 71629 non-null object\n", " 29 prs_gn1 71629 non-null object\n", " 30 prs_nu1 71629 non-null object\n", " 31 prs_ps1 71629 non-null object\n", " 32 ps1 71629 non-null object\n", " 33 rank_occ1 71629 non-null int64 \n", " 34 sp1 71629 non-null object\n", " 35 st1 16658 non-null object\n", " 36 uvf1 71629 non-null object\n", " 37 vbe1 22110 non-null object\n", " 38 vbs1 71629 non-null object\n", " 39 vs1 71629 non-null object\n", " 40 vt1 71629 non-null object\n", " 41 paragogicNun 71629 non-null bool \n", " 42 emphaticImpv 71629 non-null bool \n", " 43 Transposition 71629 non-null bool \n", " 44 WayCohortEnding 71629 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71629 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71629 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.4+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Excluding Piel/Pual/Hitpael without DF and without compensatory lengtheninbg" ] }, { "cell_type": "code", "execution_count": 152, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[False, True]\n" ] } ], "source": [ "vt=BHSallVerbalMorphologyOTST551_552_625.PielPualHit_wo_DF_compLengthening.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 153, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 153, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " (~BHSallVerbalMorphologyOTST551_552_625['PielPualHit_wo_DF_compLengthening']==True)\n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 154, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [R, S1, S2, S3, NODE1, TYPE1, TEXT1, bol_bhsa_word_order1, bol_dict_EN1, bol_dict_HebArm1, bol_dict_abc1, bol_dict_vc1, bol_lexeme_occurrences1, bol_monad_num1, bol_qere_presence1, bol_vt1, dagesh1, freq_lex1, freq_occ1, g_word_noaccent1, gn1, language1, lex1, nme1, nu1, number1, pdp1, pfm1, prs1, prs_gn1, prs_nu1, prs_ps1, ps1, rank_occ1, sp1, st1, uvf1, vbe1, vbs1, vs1, vt1, paragogicNun, emphaticImpv, Transposition, WayCohortEnding, PielPualHit_wo_DF_compLengthening, PielPualHit_w_DoubleDoubling]\n", "Index: []" ] }, "execution_count": 154, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625[(BHSallVerbalMorphologyOTST551_552_625['PielPualHit_wo_DF_compLengthening']==True)].head()" ] }, { "cell_type": "code", "execution_count": 155, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71390 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71390 non-null int64 \n", " 1 S1 71390 non-null object\n", " 2 S2 71390 non-null int64 \n", " 3 S3 71390 non-null int64 \n", " 4 NODE1 71390 non-null int64 \n", " 5 TYPE1 71390 non-null object\n", " 6 TEXT1 71390 non-null object\n", " 7 bol_bhsa_word_order1 71390 non-null int64 \n", " 8 bol_dict_EN1 71390 non-null object\n", " 9 bol_dict_HebArm1 71390 non-null object\n", " 10 bol_dict_abc1 71390 non-null int64 \n", " 11 bol_dict_vc1 71390 non-null object\n", " 12 bol_lexeme_occurrences1 71390 non-null int64 \n", " 13 bol_monad_num1 71390 non-null int64 \n", " 14 bol_qere_presence1 71390 non-null int64 \n", " 15 bol_vt1 71390 non-null object\n", " 16 dagesh1 25185 non-null object\n", " 17 freq_lex1 71390 non-null int64 \n", " 18 freq_occ1 71390 non-null int64 \n", " 19 g_word_noaccent1 71390 non-null object\n", " 20 gn1 71390 non-null object\n", " 21 language1 71390 non-null object\n", " 22 lex1 71390 non-null object\n", " 23 nme1 61256 non-null object\n", " 24 nu1 71390 non-null object\n", " 25 number1 71390 non-null int64 \n", " 26 pdp1 71390 non-null object\n", " 27 pfm1 60457 non-null object\n", " 28 prs1 71390 non-null object\n", " 29 prs_gn1 71390 non-null object\n", " 30 prs_nu1 71390 non-null object\n", " 31 prs_ps1 71390 non-null object\n", " 32 ps1 71390 non-null object\n", " 33 rank_occ1 71390 non-null int64 \n", " 34 sp1 71390 non-null object\n", " 35 st1 16577 non-null object\n", " 36 uvf1 71390 non-null object\n", " 37 vbe1 21988 non-null object\n", " 38 vbs1 71390 non-null object\n", " 39 vs1 71390 non-null object\n", " 40 vt1 71390 non-null object\n", " 41 paragogicNun 71390 non-null bool \n", " 42 emphaticImpv 71390 non-null bool \n", " 43 Transposition 71390 non-null bool \n", " 44 WayCohortEnding 71390 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71390 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71390 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.3+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Excluding Piel/Pual/Hitpael with double doubling" ] }, { "cell_type": "code", "execution_count": 156, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[False, True]\n" ] } ], "source": [ "dd=BHSallVerbalMorphologyOTST551_552_625.PielPualHit_w_DoubleDoubling.unique().tolist()\n", "print(dd)" ] }, { "cell_type": "code", "execution_count": 157, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 157, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " (~BHSallVerbalMorphologyOTST551_552_625['PielPualHit_w_DoubleDoubling']==True)\n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 158, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [R, S1, S2, S3, NODE1, TYPE1, TEXT1, bol_bhsa_word_order1, bol_dict_EN1, bol_dict_HebArm1, bol_dict_abc1, bol_dict_vc1, bol_lexeme_occurrences1, bol_monad_num1, bol_qere_presence1, bol_vt1, dagesh1, freq_lex1, freq_occ1, g_word_noaccent1, gn1, language1, lex1, nme1, nu1, number1, pdp1, pfm1, prs1, prs_gn1, prs_nu1, prs_ps1, ps1, rank_occ1, sp1, st1, uvf1, vbe1, vbs1, vs1, vt1, paragogicNun, emphaticImpv, Transposition, WayCohortEnding, PielPualHit_wo_DF_compLengthening, PielPualHit_w_DoubleDoubling]\n", "Index: []" ] }, "execution_count": 158, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625[(BHSallVerbalMorphologyOTST551_552_625['PielPualHit_w_DoubleDoubling']==True)].head()" ] }, { "cell_type": "code", "execution_count": 159, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71386 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71386 non-null int64 \n", " 1 S1 71386 non-null object\n", " 2 S2 71386 non-null int64 \n", " 3 S3 71386 non-null int64 \n", " 4 NODE1 71386 non-null int64 \n", " 5 TYPE1 71386 non-null object\n", " 6 TEXT1 71386 non-null object\n", " 7 bol_bhsa_word_order1 71386 non-null int64 \n", " 8 bol_dict_EN1 71386 non-null object\n", " 9 bol_dict_HebArm1 71386 non-null object\n", " 10 bol_dict_abc1 71386 non-null int64 \n", " 11 bol_dict_vc1 71386 non-null object\n", " 12 bol_lexeme_occurrences1 71386 non-null int64 \n", " 13 bol_monad_num1 71386 non-null int64 \n", " 14 bol_qere_presence1 71386 non-null int64 \n", " 15 bol_vt1 71386 non-null object\n", " 16 dagesh1 25184 non-null object\n", " 17 freq_lex1 71386 non-null int64 \n", " 18 freq_occ1 71386 non-null int64 \n", " 19 g_word_noaccent1 71386 non-null object\n", " 20 gn1 71386 non-null object\n", " 21 language1 71386 non-null object\n", " 22 lex1 71386 non-null object\n", " 23 nme1 61252 non-null object\n", " 24 nu1 71386 non-null object\n", " 25 number1 71386 non-null int64 \n", " 26 pdp1 71386 non-null object\n", " 27 pfm1 60453 non-null object\n", " 28 prs1 71386 non-null object\n", " 29 prs_gn1 71386 non-null object\n", " 30 prs_nu1 71386 non-null object\n", " 31 prs_ps1 71386 non-null object\n", " 32 ps1 71386 non-null object\n", " 33 rank_occ1 71386 non-null int64 \n", " 34 sp1 71386 non-null object\n", " 35 st1 16577 non-null object\n", " 36 uvf1 71386 non-null object\n", " 37 vbe1 21986 non-null object\n", " 38 vbs1 71386 non-null object\n", " 39 vs1 71386 non-null object\n", " 40 vt1 71386 non-null object\n", " 41 paragogicNun 71386 non-null bool \n", " 42 emphaticImpv 71386 non-null bool \n", " 43 Transposition 71386 non-null bool \n", " 44 WayCohortEnding 71386 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71386 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71386 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.3+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Excluding Inf.Abs preceded by Prepositions" ] }, { "cell_type": "code", "execution_count": 131, "metadata": { "ExecuteTime": { "end_time": "2023-01-16T22:42:59.491507Z", "start_time": "2023-01-16T22:42:52.195326Z" }, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 9.94s 36 results\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
npphrasewordword
1Numbers 11:25כְּנֹ֤וחַ כְּנֹ֤וחַ
2Deuteronomy 3:5לְבַ֛ד מֵעָרֵ֥י הַפְּרָזִ֖י הַרְבֵּ֥ה מְאֹֽד׃ פְּרָזִ֖י הַרְבֵּ֥ה
3Deuteronomy 32:8בְּהַנְחֵ֤ל בְּהַנְחֵ֤ל
4Joshua 2:16עַ֚ד שֹׁ֣וב עַ֚ד שֹׁ֣וב
5Joshua 3:13כְּנֹ֣וחַ כְּנֹ֣וחַ
6Joshua 22:8בִּנְכָסִ֨ים רַבִּ֜ים וּבְמִקְנֶ֣ה רַב־מְאֹ֔ד בְּכֶ֨סֶף וּבְזָהָ֜ב וּבִנְחֹ֧שֶׁת וּבְבַרְזֶ֛ל וּבִשְׂלָמֹ֖ות הַרְבֵּ֣ה מְאֹ֑ד שְׂלָמֹ֖ות הַרְבֵּ֣ה
7Judges 13:21לְהֵרָאֹ֖ה לְהֵרָאֹ֖ה
81_Samuel 1:9אַחֲרֵ֣י שָׁתֹ֑ה אַחֲרֵ֣י שָׁתֹ֑ה
91_Samuel 3:21לְהֵרָאֹ֣ה לְהֵרָאֹ֣ה
101_Kings 5:9תְבוּנָ֖ה הַרְבֵּ֣ה מְאֹ֑ד וְרֹ֣חַב לֵ֔ב כַּחֹ֕ול תְבוּנָ֖ה הַרְבֵּ֣ה
111_Kings 10:10מֵאָ֥ה וְעֶשְׂרִ֣ים׀ כִּכַּ֣ר זָהָ֗ב וּבְשָׂמִ֛ים הַרְבֵּ֥ה מְאֹ֖ד וְאֶ֣בֶן יְקָרָ֑ה בְשָׂמִ֛ים הַרְבֵּ֥ה
121_Kings 10:11עֲצֵ֧י אַלְמֻגִּ֛ים הַרְבֵּ֥ה מְאֹ֖ד וְאֶ֥בֶן יְקָרָֽה׃ אַלְמֻגִּ֛ים הַרְבֵּ֥ה
132_Kings 13:17עַד־כַּלֵּֽה׃ עַד־כַּלֵּֽה׃
142_Kings 13:19עַד־כַּלֵּ֑ה עַד־כַּלֵּ֑ה
15Isaiah 7:2כְּנֹ֥ועַ כְּנֹ֥ועַ
16Isaiah 30:2לָעֹוז֙ לָעֹוז֙
17Isaiah 30:15בְּהַשְׁקֵט֙ וּבְבִטְחָ֔ה בְּהַשְׁקֵט֙
18Jeremiah 42:2מֵֽהַרְבֵּ֔ה מֵֽהַרְבֵּ֔ה
19Jeremiah 44:19לְהַסֵּ֥ךְ לְהַסֵּ֥ךְ
20Jeremiah 44:25לְהַסֵּ֥ךְ לְהַסֵּ֥ךְ
21Ezekiel 16:49גָּאֹ֨ון שִׂבְעַת־לֶ֜חֶם וְשַׁלְוַ֣ת הַשְׁקֵ֗ט שַׁלְוַ֣ת הַשְׁקֵ֗ט
22Haggai 1:9אֶל־הַרְבֵּה֙ אֶל־הַרְבֵּה֙
23Psalms 38:17בְּמֹ֥וט בְּמֹ֥וט
24Psalms 46:3בְמֹ֥וט בְמֹ֥וט
25Job 34:35בְהַשְׂכֵּֽיל׃ בְהַשְׂכֵּֽיל׃
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "InfAbs='''\n", "phrase\n", " w1:word sp=prep|subs|art\n", " w2:word bol_monad_num* bol_qere_presence* bol_lexeme_occurrences* bol_vt* dagesh* lex* number* vbe* vbs* uvf* prs* pfm* nme* freq_occ* freq_lex* st* rank_occ* bol_dict_abc* bol_dict_HebArm* bol_bhsa_word_order* bol_dict_vc* ps* nu* gn* vt=infa vs prs_nu* prs_ps* prs_gn* sp=verb pdp* bol_dict_EN* g_word_noaccent* language* \n", "\n", "w1 <: w2\n", "\n", "'''\n", "InfAbs = BHSa4c.search(InfAbs)\n", "BHSa4c.table(InfAbs, start=1, end=25, multiFeatures=True, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": 132, "metadata": { "ExecuteTime": { "end_time": "2022-06-02T19:51:07.031470Z", "start_time": "2022-06-02T19:50:56.289207Z" } }, "outputs": [], "source": [ "BHSa4c.export(InfAbs, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='ProblematicInfAbs.tsv')" ] }, { "cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1NODE2TYPE2TEXT2sp2NODE3TYPE3TEXT3bol_bhsa_word_order3bol_dict_EN3bol_dict_HebArm3bol_dict_abc3bol_dict_vc3bol_lexeme_occurrences3bol_monad_num3bol_qere_presence3bol_vt3dagesh3freq_lex3freq_occ3g_word_noaccent3gn3language3lex3nme3nu3number3pdp3pfm3prs3prs_gn3prs_nu3prs_ps3ps3rank_occ3sp3st3uvf3vbe3vbs3vs3vt3
01Numbers1125695847phraseכְּנֹ֤וחַ77359wordכְּprep77360wordנֹ֤וחַ77360qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural141773590infaNaN1417NOWXAunknownHebrewNWX[NaNunknown7750verbNaNabsentunknownunknownunknownunknown4072verbaabsentNaNabsentqalinfa
12Deuteronomy35705225phraseלְבַ֛ד מֵעָרֵ֥י הַפְּרָזִ֖י הַרְבֵּ֥ה מְאֹֽד׃94607wordפְּרָזִ֖יsubs94608wordהַרְבֵּ֥ה94608qal: be numerous, become numerous, be great; p...רבה I7129i-guttural, iii-hey224946070infa_DL22466HAR:B.;HunknownHebrewRBH[NaNunknown1810advbNaNabsentunknownunknownunknownunknown607verbaabsentNaNHhifinfa
23Deuteronomy328714859phraseבְּהַנְחֵ֤ל111542wordבְּprep111543wordהַנְחֵ֤ל111543qal: obtain, receive property; pi: divide as p...נחל5023i-nun, ii-guttural591115420infaNaN591HAN:X;LunknownHebrewNXL[NaNunknown18745verbNaNabsentunknownunknownunknownunknown12851verbaabsentNaNHhifinfa
34Joshua216716230phraseעַ֚ד שֹׁ֣וב113743wordעַ֚דprep113744wordשֹׁ֣וב113744qal: turn, return, repeat; pi: bring back; sed...שׁוב I7576ii-waw10371137430infaNaN103885COWBunknownHebrewCWB[NaNunknown819verbNaNabsentunknownunknownunknownunknown481verbaabsentNaNabsentqalinfa
45Joshua313716503phraseכְּנֹ֣וחַ114223wordכְּprep114224wordנֹ֣וחַ114224qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1411142230infaNaN1417NOWXAunknownHebrewNWX[NaNunknown1299verbNaNabsentunknownunknownunknownunknown4072verbaabsentNaNabsentqalinfa
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "0 1 Numbers 11 25 695847 phrase \n", "1 2 Deuteronomy 3 5 705225 phrase \n", "2 3 Deuteronomy 32 8 714859 phrase \n", "3 4 Joshua 2 16 716230 phrase \n", "4 5 Joshua 3 13 716503 phrase \n", "\n", " TEXT1 NODE2 TYPE2 TEXT2 \\\n", "0 כְּנֹ֤וחַ 77359 word כְּ \n", "1 לְבַ֛ד מֵעָרֵ֥י הַפְּרָזִ֖י הַרְבֵּ֥ה מְאֹֽד׃ 94607 word פְּרָזִ֖י \n", "2 בְּהַנְחֵ֤ל 111542 word בְּ \n", "3 עַ֚ד שֹׁ֣וב 113743 word עַ֚ד \n", "4 כְּנֹ֣וחַ 114223 word כְּ \n", "\n", " sp2 NODE3 TYPE3 TEXT3 bol_bhsa_word_order3 \\\n", "0 prep 77360 word נֹ֤וחַ 77360 \n", "1 subs 94608 word הַרְבֵּ֥ה 94608 \n", "2 prep 111543 word הַנְחֵ֤ל 111543 \n", "3 prep 113744 word שֹׁ֣וב 113744 \n", "4 prep 114224 word נֹ֣וחַ 114224 \n", "\n", " bol_dict_EN3 bol_dict_HebArm3 \\\n", "0 qal: rest, settle down, make quiet; hi: lay, d... נוח I \n", "1 qal: be numerous, become numerous, be great; p... רבה I \n", "2 qal: obtain, receive property; pi: divide as p... נחל \n", "3 qal: turn, return, repeat; pi: bring back; sed... שׁוב I \n", "4 qal: rest, settle down, make quiet; hi: lay, d... נוח I \n", "\n", " bol_dict_abc3 bol_dict_vc3 bol_lexeme_occurrences3 \\\n", "0 4989 i-nun, ii-waw, iii-guttural 141 \n", "1 7129 i-guttural, iii-hey 224 \n", "2 5023 i-nun, ii-guttural 59 \n", "3 7576 ii-waw 1037 \n", "4 4989 i-nun, ii-waw, iii-guttural 141 \n", "\n", " bol_monad_num3 bol_qere_presence3 bol_vt3 dagesh3 freq_lex3 freq_occ3 \\\n", "0 77359 0 infa NaN 141 7 \n", "1 94607 0 infa _DL 224 66 \n", "2 111542 0 infa NaN 59 1 \n", "3 113743 0 infa NaN 1038 85 \n", "4 114223 0 infa NaN 141 7 \n", "\n", " g_word_noaccent3 gn3 language3 lex3 nme3 nu3 number3 pdp3 \\\n", "0 NOWXA unknown Hebrew NWX[ NaN unknown 7750 verb \n", "1 HAR:B.;H unknown Hebrew RBH[ NaN unknown 1810 advb \n", "2 HAN:X;L unknown Hebrew NXL[ NaN unknown 18745 verb \n", "3 COWB unknown Hebrew CWB[ NaN unknown 819 verb \n", "4 NOWXA unknown Hebrew NWX[ NaN unknown 1299 verb \n", "\n", " pfm3 prs3 prs_gn3 prs_nu3 prs_ps3 ps3 rank_occ3 sp3 st3 \\\n", "0 NaN absent unknown unknown unknown unknown 4072 verb a \n", "1 NaN absent unknown unknown unknown unknown 607 verb a \n", "2 NaN absent unknown unknown unknown unknown 12851 verb a \n", "3 NaN absent unknown unknown unknown unknown 481 verb a \n", "4 NaN absent unknown unknown unknown unknown 4072 verb a \n", "\n", " uvf3 vbe3 vbs3 vs3 vt3 \n", "0 absent NaN absent qal infa \n", "1 absent NaN H hif infa \n", "2 absent NaN H hif infa \n", "3 absent NaN absent qal infa \n", "4 absent NaN absent qal infa " ] }, "execution_count": 133, "metadata": {}, "output_type": "execute_result" } ], "source": [ "InfAbsPrep=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/ProblematicInfAbs.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "InfAbsPrep.head()" ] }, { "cell_type": "code", "execution_count": 136, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "0 77359\n", "1 94607\n", "2 111542\n", "3 113743\n", "4 114223\n", "5 125439\n", "6 136154\n", "7 141712\n", "8 143259\n", "9 179525\n", "10 184546\n", "11 184583\n", "12 203451\n", "13 203491\n", "14 214291\n", "15 221825\n", "16 222066\n", "17 257842\n", "18 259216\n", "19 259419\n", "20 271915\n", "21 304267\n", "22 316782\n", "23 318105\n", "24 344708\n", "25 346950\n", "26 352564\n", "27 362875\n", "28 382676\n", "29 385863\n", "30 388434\n", "31 412378\n", "32 413774\n", "33 414411\n", "34 418428\n", "35 422541\n", "Name: bol_monad_num3, dtype: int64" ] }, "execution_count": 136, "metadata": {}, "output_type": "execute_result" } ], "source": [ "InfAbsPrepMonads=InfAbsPrep['bol_monad_num3']\n", "InfAbsPrepMonads.head(50)" ] }, { "cell_type": "code", "execution_count": 162, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 162, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " ~(\n", " (BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==77359)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==94607)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==111542)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==113743)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==114223)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==125439)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==136154)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==141712)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==143259)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==179525)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==184546)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==184583)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==203451)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==203491)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==214291)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==221825)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==222066)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==257842)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==259216)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==259419)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==271915)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==304267)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==316782)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==318105)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==344708)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==346950)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==352564)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==362875)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==382676)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==385863)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==388434)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==412378)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==413774)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==414411)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==418428)\n", " |(BHSallVerbalMorphologyOTST551_552_625['bol_monad_num1']==422541)\n", " ) \n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 163, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71351 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71351 non-null int64 \n", " 1 S1 71351 non-null object\n", " 2 S2 71351 non-null int64 \n", " 3 S3 71351 non-null int64 \n", " 4 NODE1 71351 non-null int64 \n", " 5 TYPE1 71351 non-null object\n", " 6 TEXT1 71351 non-null object\n", " 7 bol_bhsa_word_order1 71351 non-null int64 \n", " 8 bol_dict_EN1 71351 non-null object\n", " 9 bol_dict_HebArm1 71351 non-null object\n", " 10 bol_dict_abc1 71351 non-null int64 \n", " 11 bol_dict_vc1 71351 non-null object\n", " 12 bol_lexeme_occurrences1 71351 non-null int64 \n", " 13 bol_monad_num1 71351 non-null int64 \n", " 14 bol_qere_presence1 71351 non-null int64 \n", " 15 bol_vt1 71351 non-null object\n", " 16 dagesh1 25167 non-null object\n", " 17 freq_lex1 71351 non-null int64 \n", " 18 freq_occ1 71351 non-null int64 \n", " 19 g_word_noaccent1 71351 non-null object\n", " 20 gn1 71351 non-null object\n", " 21 language1 71351 non-null object\n", " 22 lex1 71351 non-null object\n", " 23 nme1 61252 non-null object\n", " 24 nu1 71351 non-null object\n", " 25 number1 71351 non-null int64 \n", " 26 pdp1 71351 non-null object\n", " 27 pfm1 60451 non-null object\n", " 28 prs1 71351 non-null object\n", " 29 prs_gn1 71351 non-null object\n", " 30 prs_nu1 71351 non-null object\n", " 31 prs_ps1 71351 non-null object\n", " 32 ps1 71351 non-null object\n", " 33 rank_occ1 71351 non-null int64 \n", " 34 sp1 71351 non-null object\n", " 35 st1 16542 non-null object\n", " 36 uvf1 71351 non-null object\n", " 37 vbe1 21986 non-null object\n", " 38 vbs1 71351 non-null object\n", " 39 vs1 71351 non-null object\n", " 40 vt1 71351 non-null object\n", " 41 paragogicNun 71351 non-null bool \n", " 42 emphaticImpv 71351 non-null bool \n", " 43 Transposition 71351 non-null bool \n", " 44 WayCohortEnding 71351 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71351 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71351 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.3+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Removing difficult data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### ML>[ participle forms" ] }, { "cell_type": "code", "execution_count": 164, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 164, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " ~( \n", " (BHSallVerbalMorphologyOTST551_552_625['lex1']=='ML>[')\n", " & (\n", " (BHSallVerbalMorphologyOTST551_552_625['vs1']=='piel')\n", " |(BHSallVerbalMorphologyOTST551_552_625['vs1']=='pual')\n", " |(BHSallVerbalMorphologyOTST551_552_625['vs1']=='nif')\n", " |(BHSallVerbalMorphologyOTST551_552_625['vs1']=='qal')\n", " )\n", " & (BHSallVerbalMorphologyOTST551_552_625['vt1'].str.contains('ptc')) \n", " )\n", " \n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 165, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71302 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71302 non-null int64 \n", " 1 S1 71302 non-null object\n", " 2 S2 71302 non-null int64 \n", " 3 S3 71302 non-null int64 \n", " 4 NODE1 71302 non-null int64 \n", " 5 TYPE1 71302 non-null object\n", " 6 TEXT1 71302 non-null object\n", " 7 bol_bhsa_word_order1 71302 non-null int64 \n", " 8 bol_dict_EN1 71302 non-null object\n", " 9 bol_dict_HebArm1 71302 non-null object\n", " 10 bol_dict_abc1 71302 non-null int64 \n", " 11 bol_dict_vc1 71302 non-null object\n", " 12 bol_lexeme_occurrences1 71302 non-null int64 \n", " 13 bol_monad_num1 71302 non-null int64 \n", " 14 bol_qere_presence1 71302 non-null int64 \n", " 15 bol_vt1 71302 non-null object\n", " 16 dagesh1 25167 non-null object\n", " 17 freq_lex1 71302 non-null int64 \n", " 18 freq_occ1 71302 non-null int64 \n", " 19 g_word_noaccent1 71302 non-null object\n", " 20 gn1 71302 non-null object\n", " 21 language1 71302 non-null object\n", " 22 lex1 71302 non-null object\n", " 23 nme1 61212 non-null object\n", " 24 nu1 71302 non-null object\n", " 25 number1 71302 non-null int64 \n", " 26 pdp1 71302 non-null object\n", " 27 pfm1 60402 non-null object\n", " 28 prs1 71302 non-null object\n", " 29 prs_gn1 71302 non-null object\n", " 30 prs_nu1 71302 non-null object\n", " 31 prs_ps1 71302 non-null object\n", " 32 ps1 71302 non-null object\n", " 33 rank_occ1 71302 non-null int64 \n", " 34 sp1 71302 non-null object\n", " 35 st1 16493 non-null object\n", " 36 uvf1 71302 non-null object\n", " 37 vbe1 21986 non-null object\n", " 38 vbs1 71302 non-null object\n", " 39 vs1 71302 non-null object\n", " 40 vt1 71302 non-null object\n", " 41 paragogicNun 71302 non-null bool \n", " 42 emphaticImpv 71302 non-null bool \n", " 43 Transposition 71302 non-null bool \n", " 44 WayCohortEnding 71302 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71302 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71302 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.3+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Irregular i-Yod forms in hifil (יְהֹודֶה, יְהֹודֻךָ)\n", "Some i-yod forms squeeze an unexpected Hey between the preformative and the first root consonant. A total of four exceptional forms can be found." ] }, { "cell_type": "code", "execution_count": 166, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
24565245661_Samuel1747151886wordיְהֹושִׁ֣יעַ151886ni: be saved; hi: save;ישׁע3352i-waw, iii-guttural2051518850impfNaN2052J:HOWCIJ<AmHebrewJC<[absentsg10350verbJabsentunknownunknownunknownp39178verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
5534655347Psalms4518318073wordיְ֝הֹודֻ֗ךָ318073hit: confess; hi: thank, praise, confess;ידה I2932i-waw, iii-hey1113180720impfNaN1111J:HOWDUK@mHebrewJDH[absentpl7424verbJKmsgp2p312851verbNaNabsentWHhifimpfFalseFalseFalseFalseFalseFalse
5826558266Psalms1166330935wordיְהֹושִֽׁיעַ׃330935ni: be saved; hi: save;ישׁע3352i-waw, iii-guttural2053309340impfNaN2052J:HOWCIJ<AmHebrewJC<[absentsg20286verbJabsentunknownunknownunknownp39178verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
6920869209Nehemiah1117389527wordיְהֹודֶ֣ה389527hit: confess; hi: thank, praise, confess;ידה I2932i-waw, iii-hey1113895260impfNaN111820J:HOWDEHmHebrewJDH[absentsg6113verbJabsentunknownunknownunknownp340verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "24565 24566 1_Samuel 17 47 151886 word יְהֹושִׁ֣יעַ \n", "55346 55347 Psalms 45 18 318073 word יְ֝הֹודֻ֗ךָ \n", "58265 58266 Psalms 116 6 330935 word יְהֹושִֽׁיעַ׃ \n", "69208 69209 Nehemiah 11 17 389527 word יְהֹודֶ֣ה \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "24565 151886 ni: be saved; hi: save; \n", "55346 318073 hit: confess; hi: thank, praise, confess; \n", "58265 330935 ni: be saved; hi: save; \n", "69208 389527 hit: confess; hi: thank, praise, confess; \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "24565 ישׁע 3352 i-waw, iii-guttural \n", "55346 ידה I 2932 i-waw, iii-hey \n", "58265 ישׁע 3352 i-waw, iii-guttural \n", "69208 ידה I 2932 i-waw, iii-hey \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "24565 205 151885 0 impf \n", "55346 111 318072 0 impf \n", "58265 205 330934 0 impf \n", "69208 111 389526 0 impf \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "24565 NaN 205 2 J:HOWCIJ\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
01Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
12Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
23Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
34Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
45Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "0 1 Genesis 1 1 3 word בָּרָ֣א 3 \n", "1 2 Genesis 1 2 15 word הָיְתָ֥ה 15 \n", "2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת 27 \n", "3 4 Genesis 1 3 33 word יֹּ֥אמֶר 33 \n", "4 5 Genesis 1 3 35 word יְהִ֣י 35 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "0 qal: create; ni: be created; ברא I \n", "1 qal: be, happen, become, occur; ni: be realize... היה \n", "2 qal: shake; pi: hover; רחף \n", "3 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "4 qal: be, happen, become, occur; ni: be realize... היה \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "0 1188 ii-guttural, iii-aleph 48 \n", "1 1864 i-guttural, iii-hey 3561 \n", "2 7238 i-guttural, ii-guttural 3 \n", "3 545 i-aleph 5307 \n", "4 1864 i-guttural, iii-hey 3561 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 freq_occ1 \\\n", "0 3 0 perf DL 48 15 \n", "1 15 0 perf NaN 3561 209 \n", "2 27 0 ptca NaN 3 1 \n", "3 33 0 wayq DF 5307 2160 \n", "4 35 0 juss NaN 3561 866 \n", "\n", " g_word_noaccent1 gn1 language1 lex1 nme1 nu1 number1 pdp1 pfm1 \\\n", "0 B.@R@> m Hebrew BR>[ absent sg 3 verb absent \n", "1 H@J:T@H f Hebrew HJH[ absent sg 15 verb absent \n", "2 M:RAXEPET f Hebrew RXP[ T sg 27 verb M \n", "3 J.O>MER m Hebrew >MR[ absent sg 33 verb J \n", "4 J:HIJ m Hebrew HJH[ absent sg 35 verb J \n", "\n", " prs1 prs_gn1 prs_nu1 prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 \\\n", "0 absent unknown unknown unknown p3 2341 verb NaN absent \n", "1 absent unknown unknown unknown p3 204 verb NaN absent \n", "2 absent unknown unknown unknown unknown 12851 verb a absent \n", "3 absent unknown unknown unknown p3 18 verb NaN absent \n", "4 absent unknown unknown unknown p3 38 verb NaN absent \n", "\n", " vbe1 vbs1 vs1 vt1 paragogicNun emphaticImpv Transposition \\\n", "0 NaN absent qal perf False False False \n", "1 H absent qal perf False False False \n", "2 NaN absent piel ptca False False False \n", "3 NaN absent qal wayq False False False \n", "4 NaN absent qal impf False False False \n", "\n", " WayCohortEnding PielPualHit_wo_DF_compLengthening \\\n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False \n", "\n", " PielPualHit_w_DoubleDoubling \n", "0 False \n", "1 False \n", "2 False \n", "3 False \n", "4 False " ] }, "execution_count": 167, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=BHSallVerbalMorphologyOTST551_552_625[\n", " ~( \n", " (BHSallVerbalMorphologyOTST551_552_625['g_word_noaccent1'].str.contains('^J:HOW.*'))\n", " & (BHSallVerbalMorphologyOTST551_552_625['vs1'].str.contains('^hif')) \n", " & (BHSallVerbalMorphologyOTST551_552_625['lex1'].str.contains('^J.*\\[')) \n", " )\n", " \n", " ]\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "code", "execution_count": 168, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 71298 entries, 0 to 73709\n", "Data columns (total 47 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 71298 non-null int64 \n", " 1 S1 71298 non-null object\n", " 2 S2 71298 non-null int64 \n", " 3 S3 71298 non-null int64 \n", " 4 NODE1 71298 non-null int64 \n", " 5 TYPE1 71298 non-null object\n", " 6 TEXT1 71298 non-null object\n", " 7 bol_bhsa_word_order1 71298 non-null int64 \n", " 8 bol_dict_EN1 71298 non-null object\n", " 9 bol_dict_HebArm1 71298 non-null object\n", " 10 bol_dict_abc1 71298 non-null int64 \n", " 11 bol_dict_vc1 71298 non-null object\n", " 12 bol_lexeme_occurrences1 71298 non-null int64 \n", " 13 bol_monad_num1 71298 non-null int64 \n", " 14 bol_qere_presence1 71298 non-null int64 \n", " 15 bol_vt1 71298 non-null object\n", " 16 dagesh1 25167 non-null object\n", " 17 freq_lex1 71298 non-null int64 \n", " 18 freq_occ1 71298 non-null int64 \n", " 19 g_word_noaccent1 71298 non-null object\n", " 20 gn1 71298 non-null object\n", " 21 language1 71298 non-null object\n", " 22 lex1 71298 non-null object\n", " 23 nme1 61208 non-null object\n", " 24 nu1 71298 non-null object\n", " 25 number1 71298 non-null int64 \n", " 26 pdp1 71298 non-null object\n", " 27 pfm1 60398 non-null object\n", " 28 prs1 71298 non-null object\n", " 29 prs_gn1 71298 non-null object\n", " 30 prs_nu1 71298 non-null object\n", " 31 prs_ps1 71298 non-null object\n", " 32 ps1 71298 non-null object\n", " 33 rank_occ1 71298 non-null int64 \n", " 34 sp1 71298 non-null object\n", " 35 st1 16493 non-null object\n", " 36 uvf1 71298 non-null object\n", " 37 vbe1 21985 non-null object\n", " 38 vbs1 71298 non-null object\n", " 39 vs1 71298 non-null object\n", " 40 vt1 71298 non-null object\n", " 41 paragogicNun 71298 non-null bool \n", " 42 emphaticImpv 71298 non-null bool \n", " 43 Transposition 71298 non-null bool \n", " 44 WayCohortEnding 71298 non-null bool \n", " 45 PielPualHit_wo_DF_compLengthening 71298 non-null bool \n", " 46 PielPualHit_w_DoubleDoubling 71298 non-null bool \n", "dtypes: bool(6), int64(13), object(28)\n", "memory usage: 23.3+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Exporting cleaned up data" ] }, { "cell_type": "code", "execution_count": 169, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphologyOTST551_552_625.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/cleanedupVerbalMorphology551552625.xlsx')" ] }, { "cell_type": "code", "execution_count": 170, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
001Genesis113wordבָּרָ֣א3qal: create; ni: be created;ברא I1188ii-guttural, iii-aleph4830perfDL4815B.@R@>mHebrewBR>[absentsg3verbabsentabsentunknownunknownunknownp32341verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
112Genesis1215wordהָיְתָ֥ה15qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561150perfNaN3561209H@J:T@HfHebrewHJH[absentsg15verbabsentabsentunknownunknownunknownp3204verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
223Genesis1227wordמְרַחֶ֖פֶת27qal: shake; pi: hover;רחף7238i-guttural, ii-guttural3270ptcaNaN31M:RAXEPETfHebrewRXP[Tsg27verbMabsentunknownunknownunknownunknown12851verbaabsentNaNabsentpielptcaFalseFalseFalseFalseFalseFalse
334Genesis1333wordיֹּ֥אמֶר33qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph5307330wayqDF53072160J.O>MERmHebrew>MR[absentsg33verbJabsentunknownunknownunknownp318verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
445Genesis1335wordיְהִ֣י35qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey3561350jussNaN3561866J:HIJmHebrewHJH[absentsg35verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "0 0 1 Genesis 1 1 3 word בָּרָ֣א \n", "1 1 2 Genesis 1 2 15 word הָיְתָ֥ה \n", "2 2 3 Genesis 1 2 27 word מְרַחֶ֖פֶת \n", "3 3 4 Genesis 1 3 33 word יֹּ֥אמֶר \n", "4 4 5 Genesis 1 3 35 word יְהִ֣י \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "0 3 qal: create; ni: be created; \n", "1 15 qal: be, happen, become, occur; ni: be realize... \n", "2 27 qal: shake; pi: hover; \n", "3 33 qal: say, think; ni: be said, be called; hi: d... \n", "4 35 qal: be, happen, become, occur; ni: be realize... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "0 ברא I 1188 ii-guttural, iii-aleph \n", "1 היה 1864 i-guttural, iii-hey \n", "2 רחף 7238 i-guttural, ii-guttural \n", "3 אמר I 545 i-aleph \n", "4 היה 1864 i-guttural, iii-hey \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "0 48 3 0 perf \n", "1 3561 15 0 perf \n", "2 3 27 0 ptca \n", "3 5307 33 0 wayq \n", "4 3561 35 0 juss \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 \\\n", "0 DL 48 15 B.@R@> m Hebrew BR>[ absent \n", "1 NaN 3561 209 H@J:T@H f Hebrew HJH[ absent \n", "2 NaN 3 1 M:RAXEPET f Hebrew RXP[ T \n", "3 DF 5307 2160 J.O>MER m Hebrew >MR[ absent \n", "4 NaN 3561 866 J:HIJ m Hebrew HJH[ absent \n", "\n", " nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 \\\n", "0 sg 3 verb absent absent unknown unknown unknown p3 \n", "1 sg 15 verb absent absent unknown unknown unknown p3 \n", "2 sg 27 verb M absent unknown unknown unknown unknown \n", "3 sg 33 verb J absent unknown unknown unknown p3 \n", "4 sg 35 verb J absent unknown unknown unknown p3 \n", "\n", " rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "0 2341 verb NaN absent NaN absent qal perf False \n", "1 204 verb NaN absent H absent qal perf False \n", "2 12851 verb a absent NaN absent piel ptca False \n", "3 18 verb NaN absent NaN absent qal wayq False \n", "4 38 verb NaN absent NaN absent qal impf False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "0 False False False \n", "1 False False False \n", "2 False False False \n", "3 False False False \n", "4 False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "0 False False \n", "1 False False \n", "2 False False \n", "3 False False \n", "4 False False " ] }, "execution_count": 170, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_552_625=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/cleanedupVerbalMorphology551552625.xlsx')\n", "BHSallVerbalMorphologyOTST551_552_625.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling: 2 samples of each verbal form" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### OTST551 sampling: Using `sample`" ] }, { "cell_type": "code", "execution_count": 171, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 1377 entries, 1076 to 71181\n", "Data columns (total 48 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0 1377 non-null int64 \n", " 1 R 1377 non-null int64 \n", " 2 S1 1377 non-null object\n", " 3 S2 1377 non-null int64 \n", " 4 S3 1377 non-null int64 \n", " 5 NODE1 1377 non-null int64 \n", " 6 TYPE1 1377 non-null object\n", " 7 TEXT1 1377 non-null object\n", " 8 bol_bhsa_word_order1 1377 non-null int64 \n", " 9 bol_dict_EN1 1377 non-null object\n", " 10 bol_dict_HebArm1 1377 non-null object\n", " 11 bol_dict_abc1 1377 non-null int64 \n", " 12 bol_dict_vc1 1377 non-null object\n", " 13 bol_lexeme_occurrences1 1377 non-null int64 \n", " 14 bol_monad_num1 1377 non-null int64 \n", " 15 bol_qere_presence1 1377 non-null int64 \n", " 16 bol_vt1 1377 non-null object\n", " 17 dagesh1 467 non-null object\n", " 18 freq_lex1 1377 non-null int64 \n", " 19 freq_occ1 1377 non-null int64 \n", " 20 g_word_noaccent1 1377 non-null object\n", " 21 gn1 1377 non-null object\n", " 22 language1 1377 non-null object\n", " 23 lex1 1377 non-null object\n", " 24 nme1 1193 non-null object\n", " 25 nu1 1377 non-null object\n", " 26 number1 1377 non-null int64 \n", " 27 pdp1 1377 non-null object\n", " 28 pfm1 1148 non-null object\n", " 29 prs1 1377 non-null object\n", " 30 prs_gn1 1377 non-null object\n", " 31 prs_nu1 1377 non-null object\n", " 32 prs_ps1 1377 non-null object\n", " 33 ps1 1377 non-null object\n", " 34 rank_occ1 1377 non-null int64 \n", " 35 sp1 1377 non-null object\n", " 36 st1 317 non-null object\n", " 37 uvf1 1377 non-null object\n", " 38 vbe1 405 non-null object\n", " 39 vbs1 1377 non-null object\n", " 40 vs1 1377 non-null object\n", " 41 vt1 1377 non-null object\n", " 42 paragogicNun 1377 non-null bool \n", " 43 emphaticImpv 1377 non-null bool \n", " 44 Transposition 1377 non-null bool \n", " 45 WayCohortEnding 1377 non-null bool \n", " 46 PielPualHit_wo_DF_compLengthening 1377 non-null bool \n", " 47 PielPualHit_w_DoubleDoubling 1377 non-null bool \n", "dtypes: bool(6), int64(14), object(28)\n", "memory usage: 470.7+ KB\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/03/qlrw_2h92mgd4n9sls7f84lc0000gn/T/ipykernel_43836/3841182330.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n", " BHSallVerbalMorphologyOTST551_sampled=BHSallVerbalMorphologyOTST551_552_625[\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST551_sampled=BHSallVerbalMorphologyOTST551_552_625[\n", " (BHSallVerbalMorphology['bol_lexeme_occurrences1'] > 199)\n", " & (BHSallVerbalMorphology['bol_dict_vc1'] == 'regular')\n", " ]\n", "BHSallVerbalMorphologyOTST551_sampled.info()" ] }, { "cell_type": "code", "execution_count": 172, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
107610831084Genesis1687186wordבָ֖את7186qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph257071860perfNaN257037B@>TfHebrewBW>[absentsg7186verbabsentabsentunknownunknownunknownp21046verbNaNabsentT=absentqalperfFalseFalseFalseFalseFalseFalse
107610831084Genesis1687186wordבָ֖את7186qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph257071860perfNaN257037B@>TfHebrewBW>[absentsg7186verbabsentabsentunknownunknownunknownp21046verbNaNabsentT=absentqalperfFalseFalseFalseFalseFalseFalse
107610831084Genesis1687186wordבָ֖את7186qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph257071860perfNaN257037B@>TfHebrewBW>[absentsg7186verbabsentabsentunknownunknownunknownp21046verbNaNabsentT=absentqalperfFalseFalseFalseFalseFalseFalse
136413731374Genesis19118653wordהִכּוּ֙8653ni: be hit; pu: be smitten (down); hi: smite; ...נכה5092i-nun, iii-hey50086530perfNaN50013HIK.W.unknownHebrewNKH[absentpl8653verbabsentabsentunknownunknownunknownp32594verbNaNabsentWHhifperfFalseFalseFalseFalseFalseFalse
136413731374Genesis19118653wordהִכּוּ֙8653ni: be hit; pu: be smitten (down); hi: smite; ...נכה5092i-nun, iii-hey50086530perfNaN50013HIK.W.unknownHebrewNKH[absentpl8653verbabsentabsentunknownunknownunknownp32594verbNaNabsentWHhifperfFalseFalseFalseFalseFalseFalse
136413731374Genesis19118653wordהִכּוּ֙8653ni: be hit; pu: be smitten (down); hi: smite; ...נכה5092i-nun, iii-hey50086530perfNaN50013HIK.W.unknownHebrewNKH[absentpl8653verbabsentabsentunknownunknownunknownp32594verbNaNabsentWHhifperfFalseFalseFalseFalseFalseFalse
136513741375Genesis19118663wordיִּלְא֖וּ8663qal: be weary, become weary; ni: be made weary...לאה3686ii-guttural, iii-hey1986630wayqDF191J.IL:>W.mHebrewL>H[absentpl8663verbJabsentunknownunknownunknownp312851verbNaNabsentWabsentqalwayqFalseFalseFalseFalseFalseFalse
136513741375Genesis19118663wordיִּלְא֖וּ8663qal: be weary, become weary; ni: be made weary...לאה3686ii-guttural, iii-hey1986630wayqDF191J.IL:>W.mHebrewL>H[absentpl8663verbJabsentunknownunknownunknownp312851verbNaNabsentWabsentqalwayqFalseFalseFalseFalseFalseFalse
136513741375Genesis19118663wordיִּלְא֖וּ8663qal: be weary, become weary; ni: be made weary...לאה3686ii-guttural, iii-hey1986630wayqDF191J.IL:>W.mHebrewL>H[absentpl8663verbJabsentunknownunknownunknownp312851verbNaNabsentWabsentqalwayqFalseFalseFalseFalseFalseFalse
146014711472Genesis19349166wordנַשְׁקֶ֨נּוּ9166pu: be watered; hi: give to drink;שׁקה7986iii-hey6891660impfNaN681NAC:QEN.W.unknownHebrewCQH[absentpl9166verbNHWmsgp3p112851verbNaNNNaNHhifimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "1076 1083 1084 Genesis 16 8 7186 word בָ֖את \n", "1076 1083 1084 Genesis 16 8 7186 word בָ֖את \n", "1076 1083 1084 Genesis 16 8 7186 word בָ֖את \n", "1364 1373 1374 Genesis 19 11 8653 word הִכּוּ֙ \n", "1364 1373 1374 Genesis 19 11 8653 word הִכּוּ֙ \n", "1364 1373 1374 Genesis 19 11 8653 word הִכּוּ֙ \n", "1365 1374 1375 Genesis 19 11 8663 word יִּלְא֖וּ \n", "1365 1374 1375 Genesis 19 11 8663 word יִּלְא֖וּ \n", "1365 1374 1375 Genesis 19 11 8663 word יִּלְא֖וּ \n", "1460 1471 1472 Genesis 19 34 9166 word נַשְׁקֶ֨נּוּ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "1076 7186 qal: come, enter, go in; hi: bring; let come; ... \n", "1076 7186 qal: come, enter, go in; hi: bring; let come; ... \n", "1076 7186 qal: come, enter, go in; hi: bring; let come; ... \n", "1364 8653 ni: be hit; pu: be smitten (down); hi: smite; ... \n", "1364 8653 ni: be hit; pu: be smitten (down); hi: smite; ... \n", "1364 8653 ni: be hit; pu: be smitten (down); hi: smite; ... \n", "1365 8663 qal: be weary, become weary; ni: be made weary... \n", "1365 8663 qal: be weary, become weary; ni: be made weary... \n", "1365 8663 qal: be weary, become weary; ni: be made weary... \n", "1460 9166 pu: be watered; hi: give to drink; \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "1076 בוא 889 ii-waw, iii-aleph \n", "1076 בוא 889 ii-waw, iii-aleph \n", "1076 בוא 889 ii-waw, iii-aleph \n", "1364 נכה 5092 i-nun, iii-hey \n", "1364 נכה 5092 i-nun, iii-hey \n", "1364 נכה 5092 i-nun, iii-hey \n", "1365 לאה 3686 ii-guttural, iii-hey \n", "1365 לאה 3686 ii-guttural, iii-hey \n", "1365 לאה 3686 ii-guttural, iii-hey \n", "1460 שׁקה 7986 iii-hey \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "1076 2570 7186 0 perf \n", "1076 2570 7186 0 perf \n", "1076 2570 7186 0 perf \n", "1364 500 8653 0 perf \n", "1364 500 8653 0 perf \n", "1364 500 8653 0 perf \n", "1365 19 8663 0 wayq \n", "1365 19 8663 0 wayq \n", "1365 19 8663 0 wayq \n", "1460 68 9166 0 impf \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "1076 NaN 2570 37 B@>T f Hebrew BW>[ \n", "1076 NaN 2570 37 B@>T f Hebrew BW>[ \n", "1076 NaN 2570 37 B@>T f Hebrew BW>[ \n", "1364 NaN 500 13 HIK.W. unknown Hebrew NKH[ \n", "1364 NaN 500 13 HIK.W. unknown Hebrew NKH[ \n", "1364 NaN 500 13 HIK.W. unknown Hebrew NKH[ \n", "1365 DF 19 1 J.IL:>W. m Hebrew L>H[ \n", "1365 DF 19 1 J.IL:>W. m Hebrew L>H[ \n", "1365 DF 19 1 J.IL:>W. m Hebrew L>H[ \n", "1460 NaN 68 1 NAC:QEN.W. unknown Hebrew CQH[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 \\\n", "1076 absent sg 7186 verb absent absent unknown unknown unknown \n", "1076 absent sg 7186 verb absent absent unknown unknown unknown \n", "1076 absent sg 7186 verb absent absent unknown unknown unknown \n", "1364 absent pl 8653 verb absent absent unknown unknown unknown \n", "1364 absent pl 8653 verb absent absent unknown unknown unknown \n", "1364 absent pl 8653 verb absent absent unknown unknown unknown \n", "1365 absent pl 8663 verb J absent unknown unknown unknown \n", "1365 absent pl 8663 verb J absent unknown unknown unknown \n", "1365 absent pl 8663 verb J absent unknown unknown unknown \n", "1460 absent pl 9166 verb N HW m sg p3 \n", "\n", " ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "1076 p2 1046 verb NaN absent T= absent qal perf False \n", "1076 p2 1046 verb NaN absent T= absent qal perf False \n", "1076 p2 1046 verb NaN absent T= absent qal perf False \n", "1364 p3 2594 verb NaN absent W H hif perf False \n", "1364 p3 2594 verb NaN absent W H hif perf False \n", "1364 p3 2594 verb NaN absent W H hif perf False \n", "1365 p3 12851 verb NaN absent W absent qal wayq False \n", "1365 p3 12851 verb NaN absent W absent qal wayq False \n", "1365 p3 12851 verb NaN absent W absent qal wayq False \n", "1460 p1 12851 verb NaN N NaN H hif impf False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "1076 False False False \n", "1076 False False False \n", "1076 False False False \n", "1364 False False False \n", "1364 False False False \n", "1364 False False False \n", "1365 False False False \n", "1365 False False False \n", "1365 False False False \n", "1460 False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "1076 False False \n", "1076 False False \n", "1076 False False \n", "1364 False False \n", "1364 False False \n", "1364 False False \n", "1365 False False \n", "1365 False False \n", "1365 False False \n", "1460 False False " ] }, "execution_count": 172, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHSallVerbalMorphologyOTST551_sampled=BHSallVerbalMorphologyOTST551_sampled \\\n", " .groupby(['ps1',\n", " 'gn1',\n", " 'nu1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'bol_dict_vc1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1']) \\\n", " .sample(n=3, random_state=1, replace=True)\\\n", " .sort_values(['bol_monad_num1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1'], \n", " ascending=True)\n", "BHSallVerbalMorphologyOTST551_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": 173, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
107610831084Genesis1687186wordבָ֖את7186qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph257071860perfNaN257037B@>TfHebrewBW>[absentsg7186verbabsentabsentunknownunknownunknownp21046verbNaNabsentT=absentqalperfFalseFalseFalseFalseFalseFalse
136413731374Genesis19118653wordהִכּוּ֙8653ni: be hit; pu: be smitten (down); hi: smite; ...נכה5092i-nun, iii-hey50086530perfNaN50013HIK.W.unknownHebrewNKH[absentpl8653verbabsentabsentunknownunknownunknownp32594verbNaNabsentWHhifperfFalseFalseFalseFalseFalseFalse
136513741375Genesis19118663wordיִּלְא֖וּ8663qal: be weary, become weary; ni: be made weary...לאה3686ii-guttural, iii-hey1986630wayqDF191J.IL:>W.mHebrewL>H[absentpl8663verbJabsentunknownunknownunknownp312851verbNaNabsentWabsentqalwayqFalseFalseFalseFalseFalseFalse
146014711472Genesis19349166wordנַשְׁקֶ֨נּוּ9166pu: be watered; hi: give to drink;שׁקה7986iii-hey6891660impfNaN681NAC:QEN.W.unknownHebrewCQH[absentpl9166verbNHWmsgp3p112851verbNaNNNaNHhifimpfFalseFalseFalseFalseFalseFalse
146414751476Genesis19359181wordתַּשְׁקֶ֜יןָ9181pu: be watered; hi: give to drink;שׁקה7986iii-hey6891810wayqDL682T.AC:QEJN@fHebrewCQH[absentpl9181verbT=absentunknownunknownunknownp39178verbNaNabsentNHHhifwayqFalseFalseFalseFalseFalseFalse
146614771478Genesis19359196wordתִּשְׁכַּ֣ב9196qal: lie down; have sexual intercourse; ni: be...שׁכב7704regular21291960wayqDL_DF21216T.IC:K.ABfHebrewCKB[absentsg9196verbT=absentunknownunknownunknownp32212verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
147014811482Genesis19369207wordתַּהֲרֶ֛יןָ9207qal: conceive, be pregnant; pi: conceive; pu: ...הרה1931i-guttural, ii-guttural, iii-hey4392070wayqDL431T.AH:AREJN@fHebrewHRH[absentpl9207verbT=absentunknownunknownunknownp312851verbNaNabsentNHabsentqalwayqFalseFalseFalseFalseFalseFalse
147314841485Genesis19389233wordיָ֣לְדָה9233qal: bear, bring forth; beget; qal pass: bear,...ילד3096i-waw49292330perfNaN49251J@L:D@HfHebrewJLD[absentsg9233verbabsentabsentunknownunknownunknownp3781verbNaNabsentHabsentqalperfFalseFalseFalseFalseFalseFalse
252125552556Genesis282014898wordשְׁמָרַ֨נִי֙14898qal: keep watch, guard; ni: be guarded; beware...שׁמר7869iii-guttural468148980perfNaN4686C:M@RANIJmHebrewCMR[absentsg14898verbabsentNJunknownsgp1p34554verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
274027792780Genesis302515982wordאֵ֣לְכָ֔ה15982qal: go, walk; ni: be gone, fade; pi: go, walk...הלך1879i-waw1547159820cohoNaN154721>;L:K@HunknownHebrewHLK[absentsg15982verb>absentunknownunknownunknownp11741verbNaNabsentH=absentqalimpfFalseFalseFalseFalseFalseFalse
274827882789Genesis302716019wordיְבָרֲכֵ֥נִי16019qal: bless; ni: bless oneself; pi: bless; pu: ...ברך I1225ii-guttural327160190wayqNaN3271J:B@R:AK;NIJmHebrewBRK[absentsg16019verbJNJunknownsgp1p312851verbNaNabsentNaNabsentpielwayqFalseFalseFalseFalseFalseFalse
299830413042Genesis315417410wordיִּזְבַּ֨ח17410qal: slaughter, sacrifice; pi: sacrifice;זבח1978iii-guttural134174090wayqDF_DL13418J.IZ:B.AXmHebrewZBX[absentsg17410verbJabsentunknownunknownunknownp31982verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
303930833084Genesis321017630wordאֵיטִ֥יבָה17630qal: be good, go well; hi: act right, do well;יטב3083i-yod117176290cohoNaN1171>;JVIJB@HunknownHebrewJVB[absentsg17630verb>absentunknownunknownunknownp112851verbNaNabsentH=HhifimpfFalseFalseFalseFalseFalseFalse
324132903291Genesis341518709wordנֵאֹ֣ות18709ni: agree;אות220i-guttural, ii-waw4187080impfNaN413N;>OWTunknownHebrew>WT[absentpl18709verbNabsentunknownunknownunknownp12594verbNaNabsentNaNNnifimpfFalseFalseFalseFalseFalseFalse
346235123513Genesis37920329wordחָלַ֤מְתִּֽי20329qal: become strong; dream; hi: make strong;חלם2384i-guttural29203280perf_DL297X@LAM:T.IJunknownHebrewXLM[absentsg20329verbabsentabsentunknownunknownunknownp14072verbNaNabsentTJabsentqalperfFalseFalseFalseFalseFalseFalse
346335143515Genesis371020346wordיְסַפֵּ֣ר20346qal: write, count, number; ni: be counted; pi:...ספר5469iii-guttural108203450wayqNaN10826J:SAP.;RmHebrewSPR[absentsg20346verbJabsentunknownunknownunknownp31452verbNaNabsentNaNabsentpielwayqFalseFalseFalseFalseFalseFalse
346735183519Genesis371020367wordבֹ֣וא20367qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph2570203660infaNaN2570140BOW>unknownHebrewBW>[NaNunknown20367advbNaNabsentunknownunknownunknownunknown306verbaabsentNaNabsentqalinfaFalseFalseFalseFalseFalseFalse
347435283529Genesis371320411wordאֶשְׁלָחֲךָ֣20411qal: send; ni: be sent; pi: let go; stretch ou...שׁלח7754iii-guttural847204100impfNaN8479>EC:L@X:AK@unknownHebrewCLX[absentsg20411verb>Kmsgp2p13421verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
347835323533Genesis371420422wordרְאֵ֜ה20422qal: see; get to know; look at; choose; ni: be...ראה7095i-guttural, ii-guttural, iii-hey1298204210impvNaN1298207R:>;HmHebrewR>H[absentsg20422verbNaNabsentunknownunknownunknownp2206verbNaNabsentNaNabsentqalimpvFalseFalseFalseFalseFalseFalse
350335583559Genesis372020521wordלְכ֣וּ20521qal: go, walk; ni: be gone, fade; pi: go, walk...הלך1879i-waw1547205200impvNaN154782L:KW.mHebrewHLK[absentpl20521verbNaNabsentunknownunknownunknownp2498verbNaNabsentWabsentqalimpvFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "1076 1083 1084 Genesis 16 8 7186 word בָ֖את \n", "1364 1373 1374 Genesis 19 11 8653 word הִכּוּ֙ \n", "1365 1374 1375 Genesis 19 11 8663 word יִּלְא֖וּ \n", "1460 1471 1472 Genesis 19 34 9166 word נַשְׁקֶ֨נּוּ \n", "1464 1475 1476 Genesis 19 35 9181 word תַּשְׁקֶ֜יןָ \n", "1466 1477 1478 Genesis 19 35 9196 word תִּשְׁכַּ֣ב \n", "1470 1481 1482 Genesis 19 36 9207 word תַּהֲרֶ֛יןָ \n", "1473 1484 1485 Genesis 19 38 9233 word יָ֣לְדָה \n", "2521 2555 2556 Genesis 28 20 14898 word שְׁמָרַ֨נִי֙ \n", "2740 2779 2780 Genesis 30 25 15982 word אֵ֣לְכָ֔ה \n", "2748 2788 2789 Genesis 30 27 16019 word יְבָרֲכֵ֥נִי \n", "2998 3041 3042 Genesis 31 54 17410 word יִּזְבַּ֨ח \n", "3039 3083 3084 Genesis 32 10 17630 word אֵיטִ֥יבָה \n", "3241 3290 3291 Genesis 34 15 18709 word נֵאֹ֣ות \n", "3462 3512 3513 Genesis 37 9 20329 word חָלַ֤מְתִּֽי \n", "3463 3514 3515 Genesis 37 10 20346 word יְסַפֵּ֣ר \n", "3467 3518 3519 Genesis 37 10 20367 word בֹ֣וא \n", "3474 3528 3529 Genesis 37 13 20411 word אֶשְׁלָחֲךָ֣ \n", "3478 3532 3533 Genesis 37 14 20422 word רְאֵ֜ה \n", "3503 3558 3559 Genesis 37 20 20521 word לְכ֣וּ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "1076 7186 qal: come, enter, go in; hi: bring; let come; ... \n", "1364 8653 ni: be hit; pu: be smitten (down); hi: smite; ... \n", "1365 8663 qal: be weary, become weary; ni: be made weary... \n", "1460 9166 pu: be watered; hi: give to drink; \n", "1464 9181 pu: be watered; hi: give to drink; \n", "1466 9196 qal: lie down; have sexual intercourse; ni: be... \n", "1470 9207 qal: conceive, be pregnant; pi: conceive; pu: ... \n", "1473 9233 qal: bear, bring forth; beget; qal pass: bear,... \n", "2521 14898 qal: keep watch, guard; ni: be guarded; beware... \n", "2740 15982 qal: go, walk; ni: be gone, fade; pi: go, walk... \n", "2748 16019 qal: bless; ni: bless oneself; pi: bless; pu: ... \n", "2998 17410 qal: slaughter, sacrifice; pi: sacrifice; \n", "3039 17630 qal: be good, go well; hi: act right, do well; \n", "3241 18709 ni: agree; \n", "3462 20329 qal: become strong; dream; hi: make strong; \n", "3463 20346 qal: write, count, number; ni: be counted; pi:... \n", "3467 20367 qal: come, enter, go in; hi: bring; let come; ... \n", "3474 20411 qal: send; ni: be sent; pi: let go; stretch ou... \n", "3478 20422 qal: see; get to know; look at; choose; ni: be... \n", "3503 20521 qal: go, walk; ni: be gone, fade; pi: go, walk... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "1076 בוא 889 ii-waw, iii-aleph \n", "1364 נכה 5092 i-nun, iii-hey \n", "1365 לאה 3686 ii-guttural, iii-hey \n", "1460 שׁקה 7986 iii-hey \n", "1464 שׁקה 7986 iii-hey \n", "1466 שׁכב 7704 regular \n", "1470 הרה 1931 i-guttural, ii-guttural, iii-hey \n", "1473 ילד 3096 i-waw \n", "2521 שׁמר 7869 iii-guttural \n", "2740 הלך 1879 i-waw \n", "2748 ברך I 1225 ii-guttural \n", "2998 זבח 1978 iii-guttural \n", "3039 יטב 3083 i-yod \n", "3241 אות 220 i-guttural, ii-waw \n", "3462 חלם 2384 i-guttural \n", "3463 ספר 5469 iii-guttural \n", "3467 בוא 889 ii-waw, iii-aleph \n", "3474 שׁלח 7754 iii-guttural \n", "3478 ראה 7095 i-guttural, ii-guttural, iii-hey \n", "3503 הלך 1879 i-waw \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "1076 2570 7186 0 perf \n", "1364 500 8653 0 perf \n", "1365 19 8663 0 wayq \n", "1460 68 9166 0 impf \n", "1464 68 9181 0 wayq \n", "1466 212 9196 0 wayq \n", "1470 43 9207 0 wayq \n", "1473 492 9233 0 perf \n", "2521 468 14898 0 perf \n", "2740 1547 15982 0 coho \n", "2748 327 16019 0 wayq \n", "2998 134 17409 0 wayq \n", "3039 117 17629 0 coho \n", "3241 4 18708 0 impf \n", "3462 29 20328 0 perf \n", "3463 108 20345 0 wayq \n", "3467 2570 20366 0 infa \n", "3474 847 20410 0 impf \n", "3478 1298 20421 0 impv \n", "3503 1547 20520 0 impv \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "1076 NaN 2570 37 B@>T f Hebrew BW>[ \n", "1364 NaN 500 13 HIK.W. unknown Hebrew NKH[ \n", "1365 DF 19 1 J.IL:>W. m Hebrew L>H[ \n", "1460 NaN 68 1 NAC:QEN.W. unknown Hebrew CQH[ \n", "1464 DL 68 2 T.AC:QEJN@ f Hebrew CQH[ \n", "1466 DL_DF 212 16 T.IC:K.AB f Hebrew CKB[ \n", "1470 DL 43 1 T.AH:AREJN@ f Hebrew HRH[ \n", "1473 NaN 492 51 J@L:D@H f Hebrew JLD[ \n", "2521 NaN 468 6 C:M@RANIJ m Hebrew CMR[ \n", "2740 NaN 1547 21 >;L:K@H unknown Hebrew HLK[ \n", "2748 NaN 327 1 J:B@R:AK;NIJ m Hebrew BRK[ \n", "2998 DF_DL 134 18 J.IZ:B.AX m Hebrew ZBX[ \n", "3039 NaN 117 1 >;JVIJB@H unknown Hebrew JVB[ \n", "3241 NaN 4 13 N;>OWT unknown Hebrew >WT[ \n", "3462 _DL 29 7 X@LAM:T.IJ unknown Hebrew XLM[ \n", "3463 NaN 108 26 J:SAP.;R m Hebrew SPR[ \n", "3467 NaN 2570 140 BOW> unknown Hebrew BW>[ \n", "3474 NaN 847 9 >EC:L@X:AK@ unknown Hebrew CLX[ \n", "3478 NaN 1298 207 R:>;H m Hebrew R>H[ \n", "3503 NaN 1547 82 L:KW. m Hebrew HLK[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 \\\n", "1076 absent sg 7186 verb absent absent unknown unknown \n", "1364 absent pl 8653 verb absent absent unknown unknown \n", "1365 absent pl 8663 verb J absent unknown unknown \n", "1460 absent pl 9166 verb N HW m sg \n", "1464 absent pl 9181 verb T= absent unknown unknown \n", "1466 absent sg 9196 verb T= absent unknown unknown \n", "1470 absent pl 9207 verb T= absent unknown unknown \n", "1473 absent sg 9233 verb absent absent unknown unknown \n", "2521 absent sg 14898 verb absent NJ unknown sg \n", "2740 absent sg 15982 verb > absent unknown unknown \n", "2748 absent sg 16019 verb J NJ unknown sg \n", "2998 absent sg 17410 verb J absent unknown unknown \n", "3039 absent sg 17630 verb > absent unknown unknown \n", "3241 absent pl 18709 verb N absent unknown unknown \n", "3462 absent sg 20329 verb absent absent unknown unknown \n", "3463 absent sg 20346 verb J absent unknown unknown \n", "3467 NaN unknown 20367 advb NaN absent unknown unknown \n", "3474 absent sg 20411 verb > K m sg \n", "3478 absent sg 20422 verb NaN absent unknown unknown \n", "3503 absent pl 20521 verb NaN absent unknown unknown \n", "\n", " prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 \\\n", "1076 unknown p2 1046 verb NaN absent T= absent qal perf \n", "1364 unknown p3 2594 verb NaN absent W H hif perf \n", "1365 unknown p3 12851 verb NaN absent W absent qal wayq \n", "1460 p3 p1 12851 verb NaN N NaN H hif impf \n", "1464 unknown p3 9178 verb NaN absent NH H hif wayq \n", "1466 unknown p3 2212 verb NaN absent NaN absent qal wayq \n", "1470 unknown p3 12851 verb NaN absent NH absent qal wayq \n", "1473 unknown p3 781 verb NaN absent H absent qal perf \n", "2521 p1 p3 4554 verb NaN absent NaN absent qal perf \n", "2740 unknown p1 1741 verb NaN absent H= absent qal impf \n", "2748 p1 p3 12851 verb NaN absent NaN absent piel wayq \n", "2998 unknown p3 1982 verb NaN absent NaN absent qal wayq \n", "3039 unknown p1 12851 verb NaN absent H= H hif impf \n", "3241 unknown p1 2594 verb NaN absent NaN N nif impf \n", "3462 unknown p1 4072 verb NaN absent TJ absent qal perf \n", "3463 unknown p3 1452 verb NaN absent NaN absent piel wayq \n", "3467 unknown unknown 306 verb a absent NaN absent qal infa \n", "3474 p2 p1 3421 verb NaN absent NaN absent qal impf \n", "3478 unknown p2 206 verb NaN absent NaN absent qal impv \n", "3503 unknown p2 498 verb NaN absent W absent qal impv \n", "\n", " paragogicNun emphaticImpv Transposition WayCohortEnding \\\n", "1076 False False False False \n", "1364 False False False False \n", "1365 False False False False \n", "1460 False False False False \n", "1464 False False False False \n", "1466 False False False False \n", "1470 False False False False \n", "1473 False False False False \n", "2521 False False False False \n", "2740 False False False False \n", "2748 False False False False \n", "2998 False False False False \n", "3039 False False False False \n", "3241 False False False False \n", "3462 False False False False \n", "3463 False False False False \n", "3467 False False False False \n", "3474 False False False False \n", "3478 False False False False \n", "3503 False False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "1076 False False \n", "1364 False False \n", "1365 False False \n", "1460 False False \n", "1464 False False \n", "1466 False False \n", "1470 False False \n", "1473 False False \n", "2521 False False \n", "2740 False False \n", "2748 False False \n", "2998 False False \n", "3039 False False \n", "3241 False False \n", "3462 False False \n", "3463 False False \n", "3467 False False \n", "3474 False False \n", "3478 False False \n", "3503 False False " ] }, "execution_count": 173, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_sampled.drop_duplicates(subset=\"bol_monad_num1\", keep='first', inplace=True)\n", "BHSallVerbalMorphologyOTST551_sampled.head(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST551 raw sampled data" ] }, { "cell_type": "code", "execution_count": 174, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
107610831084Genesis1687186wordבָ֖את7186qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph257071860perfNaN257037B@>TfHebrewBW>[absentsg7186verbabsentabsentunknownunknownunknownp21046verbNaNabsentT=absentqalperfFalseFalseFalseFalseFalseFalse
136413731374Genesis19118653wordהִכּוּ֙8653ni: be hit; pu: be smitten (down); hi: smite; ...נכה5092i-nun, iii-hey50086530perfNaN50013HIK.W.unknownHebrewNKH[absentpl8653verbabsentabsentunknownunknownunknownp32594verbNaNabsentWHhifperfFalseFalseFalseFalseFalseFalse
136513741375Genesis19118663wordיִּלְא֖וּ8663qal: be weary, become weary; ni: be made weary...לאה3686ii-guttural, iii-hey1986630wayqDF191J.IL:>W.mHebrewL>H[absentpl8663verbJabsentunknownunknownunknownp312851verbNaNabsentWabsentqalwayqFalseFalseFalseFalseFalseFalse
146014711472Genesis19349166wordנַשְׁקֶ֨נּוּ9166pu: be watered; hi: give to drink;שׁקה7986iii-hey6891660impfNaN681NAC:QEN.W.unknownHebrewCQH[absentpl9166verbNHWmsgp3p112851verbNaNNNaNHhifimpfFalseFalseFalseFalseFalseFalse
146414751476Genesis19359181wordתַּשְׁקֶ֜יןָ9181pu: be watered; hi: give to drink;שׁקה7986iii-hey6891810wayqDL682T.AC:QEJN@fHebrewCQH[absentpl9181verbT=absentunknownunknownunknownp39178verbNaNabsentNHHhifwayqFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "1076 1083 1084 Genesis 16 8 7186 word בָ֖את \n", "1364 1373 1374 Genesis 19 11 8653 word הִכּוּ֙ \n", "1365 1374 1375 Genesis 19 11 8663 word יִּלְא֖וּ \n", "1460 1471 1472 Genesis 19 34 9166 word נַשְׁקֶ֨נּוּ \n", "1464 1475 1476 Genesis 19 35 9181 word תַּשְׁקֶ֜יןָ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "1076 7186 qal: come, enter, go in; hi: bring; let come; ... \n", "1364 8653 ni: be hit; pu: be smitten (down); hi: smite; ... \n", "1365 8663 qal: be weary, become weary; ni: be made weary... \n", "1460 9166 pu: be watered; hi: give to drink; \n", "1464 9181 pu: be watered; hi: give to drink; \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "1076 בוא 889 ii-waw, iii-aleph \n", "1364 נכה 5092 i-nun, iii-hey \n", "1365 לאה 3686 ii-guttural, iii-hey \n", "1460 שׁקה 7986 iii-hey \n", "1464 שׁקה 7986 iii-hey \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "1076 2570 7186 0 perf \n", "1364 500 8653 0 perf \n", "1365 19 8663 0 wayq \n", "1460 68 9166 0 impf \n", "1464 68 9181 0 wayq \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "1076 NaN 2570 37 B@>T f Hebrew BW>[ \n", "1364 NaN 500 13 HIK.W. unknown Hebrew NKH[ \n", "1365 DF 19 1 J.IL:>W. m Hebrew L>H[ \n", "1460 NaN 68 1 NAC:QEN.W. unknown Hebrew CQH[ \n", "1464 DL 68 2 T.AC:QEJN@ f Hebrew CQH[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 \\\n", "1076 absent sg 7186 verb absent absent unknown unknown unknown \n", "1364 absent pl 8653 verb absent absent unknown unknown unknown \n", "1365 absent pl 8663 verb J absent unknown unknown unknown \n", "1460 absent pl 9166 verb N HW m sg p3 \n", "1464 absent pl 9181 verb T= absent unknown unknown unknown \n", "\n", " ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "1076 p2 1046 verb NaN absent T= absent qal perf False \n", "1364 p3 2594 verb NaN absent W H hif perf False \n", "1365 p3 12851 verb NaN absent W absent qal wayq False \n", "1460 p1 12851 verb NaN N NaN H hif impf False \n", "1464 p3 9178 verb NaN absent NH H hif wayq False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "1076 False False False \n", "1364 False False False \n", "1365 False False False \n", "1460 False False False \n", "1464 False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "1076 False False \n", "1364 False False \n", "1365 False False \n", "1460 False False \n", "1464 False False " ] }, "execution_count": 174, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST551_sampled.head()" ] }, { "cell_type": "code", "execution_count": 175, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAArcAAAIFCAYAAADIn9UJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy88F64QAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA6eklEQVR4nO3deVxWZf7/8fctqyggi4IU7oxpuKJjaibklrujM66Vls5YpiOm1Zhfc5vcKpfUbJkS01Ebm3C0GnPfUlNxN2syMTeIRAUXBMXz+6MH9687UAGR++bq9Xw8zuMx57qu+5zPoTM83l5c59w2y7IsAQAAAAYo5ewCAAAAgKJCuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BVCsdu7cqT/96U+qWLGiPD09FRoaqj/+8Y/asWOHs0vLlxMnTshmsykuLs7eFhcXJ5vNphMnTtz2sznjcjZ3d3fdf//9euqpp3TmzBmHsUePHtUTTzyhatWqydvbW8HBwWrYsKGGDh2q9PT0Ap3H29tboaGhiomJ0ZQpU5SSkpLrM+PHj5fNZsv3z0GSrl69qvHjx2vTpk0F+lxe56pSpYo6depUoOPcyZIlSzRr1qw8+2w2m8aPH1+k5wPgGgi3AIrNnDlz1Lx5c50+fVrTp0/XunXr9Prrr+vMmTN6+OGHNXfuXGeXWCwWLFigHTt2aO3atfrzn/+spUuXqkWLFrpy5Yokad++fYqKitLXX3+tV155RatXr9bbb7+tjh076osvvtD58+cLfJ558+apfv36mjZtmmrVqqV169Y5jB00aFCB/4Fx9epVTZgwocDhtjDnKozbhdsdO3Zo0KBB97wGAMXP3dkFAPht+PLLLxUbG6sOHTooPj5e7u7//9dP79699Yc//EHDhw9XgwYN1Lx582KrKyMjQ97e3gWetbwbkZGRatSokSQpJiZG2dnZmjRpklasWKF+/fpp1qxZKlWqlDZt2iRfX1/75/74xz9q0qRJsiyrwOeRpB49emjEiBF6+OGH1b17d3333XcKCQmRJN1///26//77i/Aqc7t69ap8fHyK5Vx38tBDDzn1/ADuHWZuARSLKVOmyGazaf78+Q7BVpLc3d311ltvyWazaerUqZKkFStWyGazaf369bmONX/+fNlsNh08eNDetmfPHnXp0kWBgYHy9vZWgwYN9K9//cvhczl/rl+zZo2efvpplS9fXj4+PsrMzNSxY8f01FNPKSIiQj4+PrrvvvvUuXNnHTp06B78NBzlBK0ffvhBkpSamio/Pz+VLVs2z/F3E8QrVaqkN954Q5cuXdI777xjb89rqcCGDRsUHR2toKAglS5dWpUqVVKPHj109epVnThxQuXLl5ckTZgwwb4EYsCAAQ7H27t3r/74xz8qICBA1atXv+W5csTHx6tu3bry9vZWtWrV9Oabbzr032oJyKZNm2Sz2eyzyNHR0frss8/0ww8/OCzRyJHXsoTDhw+ra9euCggIkLe3t+rXr6+FCxfmeZ6lS5dqzJgxCgsLk5+fn1q3bq1vv/321j94AMWGcAvgnsvOztbGjRvVqFGjW87YhYeHKyoqShs2bFB2drY6deqkChUqaMGCBbnGxsXFqWHDhqpbt64kaePGjWrevLkuXryot99+W//5z39Uv3599erVy2FtbI6nn35aHh4eWrRokT7++GN5eHjo7NmzCgoK0tSpU7V69WrNmzdP7u7uatKkyT0PLceOHZMke1hs2rSpkpKS1K9fP23evFkZGRlFer4OHTrIzc1NW7ZsueWYEydOqGPHjvL09NQHH3yg1atXa+rUqSpTpoyysrJUsWJFrV69WpI0cOBA7dixQzt27NDYsWMdjtO9e3fVqFFDy5cv19tvv33buvbv36/Y2FiNGDFC8fHxatasmYYPH67XX3+9wNf41ltvqXnz5goNDbXXdrulEN9++62aNWumI0eO6M0339Qnn3yi2rVra8CAAZo+fXqu8S+//LJ++OEH/eMf/9C7776r7777Tp07d1Z2dnaBawVQtFiWAOCeO3funK5evaqqVavedlzVqlW1a9cupaamqkKFCnr88cc1f/58paWlyd/fX9LPD1rt2rVLc+bMsX9uyJAhevDBB7Vhwwb7rHC7du107tw5vfzyy3ryySdVqtT//7d8q1atHGYtJemRRx7RI488Yt/Pzs5Wx44d9eCDD+qdd97RjBkz7vrn8Mtj37hxQ9euXdPmzZv197//Xb6+vurSpYskadSoUdqzZ4+WLl2qpUuXys3NTXXr1lWHDh00fPhwewgurDJlyig4OFhnz5695ZiEhARdu3ZNr732murVq2dv79u3r/1/R0VFSfp5ScOt/szfv39/TZgwIV91nT17Vvv27bOfr3379kpJSdGkSZM0ZMgQ+fj45Os4klS7dm2VK1dOXl5e+VqCMH78eGVlZWnjxo0KDw+X9PM/Ai5evKgJEyZo8ODB9nsw5/iLFy+277u5ualnz57avXs3Sx4AJ2PmFoDLyFlLmvPn46effloZGRn66KOP7GMWLFggLy8ve8g6duyYvvnmG/Xr10+SdOPGDfvWoUMHJSUl5Zp57dGjR65z37hxQ5MnT1bt2rXl6ekpd3d3eXp66rvvvtPRo0eL9DofeugheXh4yNfXV506dVJoaKj++9//2te/enl5KT4+Xl9//bVmzpyp3r1766efftKrr76qWrVqFclM8p3W7davX1+enp76y1/+ooULF+r48eOFOk9eP+tbefDBBx2CtPRzmE5PT9fevXsLdf782rBhg1q1amUPtjkGDBigq1ev5pr1zfmHSI6cvyLkLC0B4DyEWwD3XHBwsHx8fJSYmHjbcSdOnJCPj48CAwMl/Rx2GjdubF+akJ2drcWLF6tr1672MT/++KOkn2c7PTw8HLYhQ4ZI+nnm+JcqVqyY69zPP/+8xo4dq27dumnVqlX66quvtHv3btWrV6/IlwV8+OGH2r17t/bt26ezZ8/q4MGDeT5EV6tWLcXGxmrx4sU6efKkZsyYodTU1Fx/+i+oK1euKDU1VWFhYbccU716da1bt04VKlTQc889p+rVq6t69eqaPXt2gc6V18/6VkJDQ2/ZlpqaWqDzFlRqamqeteb8jH59/qCgIId9Ly8vSSryewVAwbEsAcA95+bmppiYGK1evVqnT5/Oc93t6dOnlZCQoPbt28vNzc3e/tRTT2nIkCE6evSojh8/rqSkJD311FP2/uDgYEnS6NGj1b179zzPX7NmTYf9vB5mWrx4sZ588klNnjzZof3cuXMqV65cvq81P2rVquXwFoP8sNlsGjFihCZOnKjDhw/f1fk/++wzZWdnKzo6+rbjWrRooRYtWig7O1t79uzRnDlzFBsbq5CQEPXu3TvfdedXcnLyLdtywqS3t7ckKTMz02Hcr/8BU1BBQUFKSkrK1Z6zdCPnPgPg+pi5BVAsRo8eLcuyNGTIkFwP3WRnZ+vZZ5+VZVkaPXq0Q1+fPn3k7e2tuLg4xcXF6b777lPbtm3t/TVr1lRERIQOHDigRo0a5bn98nVat2Kz2eyzbzk+++yzXF+uUBzyClnSz0ErPT39tjOud3Ly5EmNGjVK/v7+Gjx4cL4+4+bmpiZNmmjevHmSZF8iUNSzlUeOHNGBAwcc2pYsWSJfX181bNhQ0s9f9iDJ4U0ZkrRy5cpcx/Py8sp3ba1atdKGDRtyrUP+8MMP5ePjwzpaoARh5hZAsWjevLlmzZql2NhYPfzwwxo6dKgqVaqkkydPat68efrqq680a9YsNWvWzOFz5cqV0x/+8AfFxcXp4sWLGjVqlMPDYZL0zjvvqH379mrXrp0GDBig++67T+fPn9fRo0e1d+9eLV++/I71derUSXFxcXrggQdUt25dJSQk6LXXXnPK+1j/8pe/6OLFi+rRo4ciIyPl5uamb775RjNnzlSpUqX00ksv5es4hw8ftq8/TklJ0datW7VgwQK5ubkpPj7+tg+mvf3229qwYYM6duyoSpUq6dq1a/rggw8kSa1bt5Yk+fr6qnLlyvrPf/6jVq1aKTAwUMHBwfYAWlBhYWHq0qWLxo8fr4oVK2rx4sVau3atpk2bZn+YrHHjxqpZs6ZGjRqlGzduKCAgQPHx8dq2bVuu49WpU0effPKJ5s+fr6ioKJUqVeqWM+bjxo3Tp59+qpiYGL3yyisKDAzUP//5T3322WeaPn26w8NkAFwb4RZAsRk2bJgaN26sN954QyNHjlRqaqoCAwP18MMPa9u2bWratGmen3vqqae0dOlSSbK/R/WXYmJitGvXLr366quKjY3VhQsXFBQUpNq1a6tnz575qm327Nny8PDQlClTdPnyZTVs2FCffPKJ/u///q/Q11tYw4YN00cffaT33ntPZ86c0ZUrV1S+fHk1bdpUH374Yb5nEXOWb3h6eqpcuXKqVauWXnrpJQ0aNOiOb1yoX7++1qxZo3Hjxik5OVlly5ZVZGSkVq5c6TBz/v777+uFF15Qly5dlJmZqf79++f5+rX8qF+/vp566imNGzdO3333ncLCwjRjxgyNGDHCPsbNzU2rVq3S0KFD9cwzz8jLy0u9e/fW3Llz1bFjR4fjDR8+XEeOHNHLL7+stLQ0WZZ1ywfpatasqe3bt+vll1/Wc889p4yMDNWqVUsLFizI854D4LpsVn6/6gYAAABwcay5BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGPwnltJN2/e1NmzZ+Xr61ugr4oEAABA8bAsS5cuXVJYWFiuL/P5JcKtfv5Ky/DwcGeXAQAAgDs4derUbb89knAr2b93/tSpU/Lz83NyNQAAAPi19PR0hYeH23PbrRBuJftSBD8/P8ItAACAC7vTElIeKAMAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMd2cXgDvr3NnZFZQ8q1Y5uwIAAOAMzNwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGMNlwu2UKVNks9kUGxtrb7MsS+PHj1dYWJhKly6t6OhoHTlyxOFzmZmZGjZsmIKDg1WmTBl16dJFp0+fLubqAQAA4ApcItzu3r1b7777rurWrevQPn36dM2YMUNz587V7t27FRoaqjZt2ujSpUv2MbGxsYqPj9eyZcu0bds2Xb58WZ06dVJ2dnZxXwYAAACczOnh9vLly+rXr5/ee+89BQQE2Nsty9KsWbM0ZswYde/eXZGRkVq4cKGuXr2qJUuWSJLS0tL0/vvv64033lDr1q3VoEEDLV68WIcOHdK6deucdUkAAABwEqeH2+eee04dO3ZU69atHdoTExOVnJystm3b2tu8vLzUsmVLbd++XZKUkJCg69evO4wJCwtTZGSkfUxeMjMzlZ6e7rABAACg5HN35smXLVumvXv3avfu3bn6kpOTJUkhISEO7SEhIfrhhx/sYzw9PR1mfHPG5Hw+L1OmTNGECRPutnwAAAC4GKfN3J46dUrDhw/X4sWL5e3tfctxNpvNYd+yrFxtv3anMaNHj1ZaWpp9O3XqVMGKBwAAgEtyWrhNSEhQSkqKoqKi5O7uLnd3d23evFlvvvmm3N3d7TO2v56BTUlJsfeFhoYqKytLFy5cuOWYvHh5ecnPz89hAwAAQMnntHDbqlUrHTp0SPv377dvjRo1Ur9+/bR//35Vq1ZNoaGhWrt2rf0zWVlZ2rx5s5o1ayZJioqKkoeHh8OYpKQkHT582D4GAAAAvx1OW3Pr6+uryMhIh7YyZcooKCjI3h4bG6vJkycrIiJCERERmjx5snx8fNS3b19Jkr+/vwYOHKiRI0cqKChIgYGBGjVqlOrUqZPrATUAAACYz6kPlN3Jiy++qIyMDA0ZMkQXLlxQkyZNtGbNGvn6+trHzJw5U+7u7urZs6cyMjLUqlUrxcXFyc3NzYmVAwAAwBlslmVZzi7C2dLT0+Xv76+0tDSXXH/bubOzKyh5Vq1ydgUAAKAo5TevOf09twAAAEBRIdwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABjDqeF2/vz5qlu3rvz8/OTn56emTZvqv//9r73fsiyNHz9eYWFhKl26tKKjo3XkyBGHY2RmZmrYsGEKDg5WmTJl1KVLF50+fbq4LwUAAAAuwKnh9v7779fUqVO1Z88e7dmzR48++qi6du1qD7DTp0/XjBkzNHfuXO3evVuhoaFq06aNLl26ZD9GbGys4uPjtWzZMm3btk2XL19Wp06dlJ2d7azLAgAAgJPYLMuynF3ELwUGBuq1117T008/rbCwMMXGxuqll16S9PMsbUhIiKZNm6bBgwcrLS1N5cuX16JFi9SrVy9J0tmzZxUeHq7PP/9c7dq1y9c509PT5e/vr7S0NPn5+d2zayuszp2dXUHJs2qVsysAAABFKb95zWXW3GZnZ2vZsmW6cuWKmjZtqsTERCUnJ6tt27b2MV5eXmrZsqW2b98uSUpISND169cdxoSFhSkyMtI+Ji+ZmZlKT0932AAAAFDyOT3cHjp0SGXLlpWXl5eeeeYZxcfHq3bt2kpOTpYkhYSEOIwPCQmx9yUnJ8vT01MBAQG3HJOXKVOmyN/f376Fh4cX8VUBAADAGZwebmvWrKn9+/dr586devbZZ9W/f399/fXX9n6bzeYw3rKsXG2/dqcxo0ePVlpamn07derU3V0EAAAAXILTw62np6dq1KihRo0aacqUKapXr55mz56t0NBQSco1A5uSkmKfzQ0NDVVWVpYuXLhwyzF58fLysr+hIWcDAABAyef0cPtrlmUpMzNTVatWVWhoqNauXWvvy8rK0ubNm9WsWTNJUlRUlDw8PBzGJCUl6fDhw/YxAAAA+O1wd+bJX375ZbVv317h4eG6dOmSli1bpk2bNmn16tWy2WyKjY3V5MmTFRERoYiICE2ePFk+Pj7q27evJMnf318DBw7UyJEjFRQUpMDAQI0aNUp16tRR69atnXlpAAAAcAKnhtsff/xRTzzxhJKSkuTv76+6detq9erVatOmjSTpxRdfVEZGhoYMGaILFy6oSZMmWrNmjXx9fe3HmDlzptzd3dWzZ09lZGSoVatWiouLk5ubm7MuCwAAAE7icu+5dQbec2se3nMLAIBZStx7bgEAAIC7RbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgjEKF22rVqik1NTVX+8WLF1WtWrW7LgoAAAAojEKF2xMnTig7OztXe2Zmps6cOXPXRQEAAACF4V6QwStXrrT/7y+++EL+/v72/ezsbK1fv15VqlQpsuIAAACAgihQuO3WrZskyWazqX///g59Hh4eqlKlit54440iKw4AAAAoiAKF25s3b0qSqlatqt27dys4OPieFAUAAAAURoHCbY7ExMSirgMAAAC4a4UKt5K0fv16rV+/XikpKfYZ3RwffPDBXRcGAAAAFFShwu2ECRM0ceJENWrUSBUrVpTNZivqugAAAIACK1S4ffvttxUXF6cnnniiqOsBAAAACq1Q77nNyspSs2bNiroWAAAA4K4UKtwOGjRIS5YsKepaAAAAgLtSqGUJ165d07vvvqt169apbt268vDwcOifMWNGkRQHAAAAFEShwu3BgwdVv359SdLhw4cd+ni4DAAAAM5SqHC7cePGoq4DAAAAuGuFWnMLAAAAuKJCzdzGxMTcdvnBhg0bCl0QAAAAUFiFCrc5621zXL9+Xfv379fhw4fVv3//oqgLAAAAKLBChduZM2fm2T5+/Hhdvnz5rgoCAAAACqtI19w+/vjj+uCDD4rykAAAAEC+FWm43bFjh7y9vYvykAAAAEC+FWpZQvfu3R32LctSUlKS9uzZo7FjxxZJYQAAAEBBFSrc+vv7O+yXKlVKNWvW1MSJE9W2bdsiKQwAAAAoqEKF2wULFhR1HQAAAMBdK1S4zZGQkKCjR4/KZrOpdu3aatCgQVHVBQAAABRYocJtSkqKevfurU2bNqlcuXKyLEtpaWmKiYnRsmXLVL58+aKuE0Ax6NzZ2RWUPKtWObsCAMAvFeptCcOGDVN6erqOHDmi8+fP68KFCzp8+LDS09P117/+tahrBAAAAPKlUDO3q1ev1rp161SrVi17W+3atTVv3jweKAMAAIDTFGrm9ubNm/Lw8MjV7uHhoZs3b951UQAAAEBhFCrcPvrooxo+fLjOnj1rbztz5oxGjBihVq1aFVlxAAAAQEEUKtzOnTtXly5dUpUqVVS9enXVqFFDVatW1aVLlzRnzpyirhEAAADIl0KtuQ0PD9fevXu1du1affPNN7IsS7Vr11br1q2Luj4AAAAg3wo0c7thwwbVrl1b6enpkqQ2bdpo2LBh+utf/6rGjRvrwQcf1NatW+9JoQAAAMCdFCjczpo1S3/+85/l5+eXq8/f31+DBw/WjBkziqw4AAAAoCAKFG4PHDigxx577Jb9bdu2VUJCwl0XBQAAABRGgcLtjz/+mOcrwHK4u7vrp59+uuuiAAAAgMIoULi97777dOjQoVv2Hzx4UBUrVrzrogAAAIDCKFC47dChg1555RVdu3YtV19GRobGjRunTp06FVlxAAAAQEEU6FVg//d//6dPPvlEv/vd7zR06FDVrFlTNptNR48e1bx585Sdna0xY8bcq1oBAACA2ypQuA0JCdH27dv17LPPavTo0bIsS5Jks9nUrl07vfXWWwoJCbknhQIAAAB3UuAvcahcubI+//xzXbhwQceOHZNlWYqIiFBAQMC9qA8AAADIt0J9Q5kkBQQEqHHjxkVZCwAAAHBXCvRAGQAAAODKCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADCGU8PtlClT1LhxY/n6+qpChQrq1q2bvv32W4cxlmVp/PjxCgsLU+nSpRUdHa0jR444jMnMzNSwYcMUHBysMmXKqEuXLjp9+nRxXgoAAABcgFPD7ebNm/Xcc89p586dWrt2rW7cuKG2bdvqypUr9jHTp0/XjBkzNHfuXO3evVuhoaFq06aNLl26ZB8TGxur+Ph4LVu2TNu2bdPly5fVqVMnZWdnO+OyAAAA4CQ2y7IsZxeR46efflKFChW0efNmPfLII7IsS2FhYYqNjdVLL70k6edZ2pCQEE2bNk2DBw9WWlqaypcvr0WLFqlXr16SpLNnzyo8PFyff/652rVrd8fzpqeny9/fX2lpafLz87un11gYnTs7u4KSZ9UqZ1dQMnGvFRz3GgAUj/zmNZdac5uWliZJCgwMlCQlJiYqOTlZbdu2tY/x8vJSy5YttX37dklSQkKCrl+/7jAmLCxMkZGR9jG/lpmZqfT0dIcNAAAAJZ/LhFvLsvT888/r4YcfVmRkpCQpOTlZkhQSEuIwNiQkxN6XnJwsT09PBQQE3HLMr02ZMkX+/v72LTw8vKgvBwAAAE7gMuF26NChOnjwoJYuXZqrz2azOexblpWr7dduN2b06NFKS0uzb6dOnSp84QAAAHAZLhFuhw0bppUrV2rjxo26//777e2hoaGSlGsGNiUlxT6bGxoaqqysLF24cOGWY37Ny8tLfn5+DhsAAABKPqeGW8uyNHToUH3yySfasGGDqlat6tBftWpVhYaGau3atfa2rKwsbd68Wc2aNZMkRUVFycPDw2FMUlKSDh8+bB8DAACA3wZ3Z578ueee05IlS/Sf//xHvr6+9hlaf39/lS5dWjabTbGxsZo8ebIiIiIUERGhyZMny8fHR3379rWPHThwoEaOHKmgoCAFBgZq1KhRqlOnjlq3bu3MywMAAEAxc2q4nT9/viQpOjraoX3BggUaMGCAJOnFF19URkaGhgwZogsXLqhJkyZas2aNfH197eNnzpwpd3d39ezZUxkZGWrVqpXi4uLk5uZWXJcCAAAAF+BS77l1Ft5zax7ePVo43GsFx70GAMWjRL7nFgAAALgbhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGcHd2AQCA357OnZ1dQcmzapWzKwBKBmZuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYw93ZBQAAANwrnTs7u4KSZ9UqZ1dwd5i5BQAAgDEItwAAADCGU8Ptli1b1LlzZ4WFhclms2nFihUO/ZZlafz48QoLC1Pp0qUVHR2tI0eOOIzJzMzUsGHDFBwcrDJlyqhLly46ffp0MV4FAAAAXIVTw+2VK1dUr149zZ07N8/+6dOna8aMGZo7d652796t0NBQtWnTRpcuXbKPiY2NVXx8vJYtW6Zt27bp8uXL6tSpk7Kzs4vrMgAAAOAinPpAWfv27dW+ffs8+yzL0qxZszRmzBh1795dkrRw4UKFhIRoyZIlGjx4sNLS0vT+++9r0aJFat26tSRp8eLFCg8P17p169SuXbtiuxYAAAA4n8uuuU1MTFRycrLatm1rb/Py8lLLli21fft2SVJCQoKuX7/uMCYsLEyRkZH2MXnJzMxUenq6wwYAAICSz2XDbXJysiQpJCTEoT0kJMTel5ycLE9PTwUEBNxyTF6mTJkif39/+xYeHl7E1QMAAMAZXDbc5rDZbA77lmXlavu1O40ZPXq00tLS7NupU6eKpFYAAAA4l8uG29DQUEnKNQObkpJin80NDQ1VVlaWLly4cMsxefHy8pKfn5/DBgAAgJLPZcNt1apVFRoaqrVr19rbsrKytHnzZjVr1kySFBUVJQ8PD4cxSUlJOnz4sH0MAAAAfjuc+raEy5cv69ixY/b9xMRE7d+/X4GBgapUqZJiY2M1efJkRUREKCIiQpMnT5aPj4/69u0rSfL399fAgQM1cuRIBQUFKTAwUKNGjVKdOnXsb08AAADAb4dTw+2ePXsUExNj33/++eclSf3791dcXJxefPFFZWRkaMiQIbpw4YKaNGmiNWvWyNfX1/6ZmTNnyt3dXT179lRGRoZatWqluLg4ubm5Ffv1AAAAwLlslmVZzi7C2dLT0+Xv76+0tDSXXH/bubOzKyh5Vq1ydgUlE/dawXGvFQ73WsFxrxUO91rBueq9lt+85rJrbgEAAICCItwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4RYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AIAAMAYhFsAAAAYg3ALAAAAYxBuAQAAYAzCLQAAAIxBuAUAAIAxCLcAAAAwBuEWAAAAxiDcAgAAwBiEWwAAABjDmHD71ltvqWrVqvL29lZUVJS2bt3q7JIAAABQzIwItx999JFiY2M1ZswY7du3Ty1atFD79u118uRJZ5cGAACAYmREuJ0xY4YGDhyoQYMGqVatWpo1a5bCw8M1f/58Z5cGAACAYuTu7ALuVlZWlhISEvS3v/3Nob1t27bavn17np/JzMxUZmamfT8tLU2SlJ6efu8KvQvXrzu7gpLHRf9TujzutYLjXisc7rWC414rHO61gnPVey0np1mWddtxJT7cnjt3TtnZ2QoJCXFoDwkJUXJycp6fmTJliiZMmJCrPTw8/J7UiOLn7+/sCvBbwb2G4sK9huLi6vfapUuX5H+bIkt8uM1hs9kc9i3LytWWY/To0Xr++eft+zdv3tT58+cVFBR0y8/AUXp6usLDw3Xq1Cn5+fk5uxwYjHsNxYV7DcWFe61wLMvSpUuXFBYWdttxJT7cBgcHy83NLdcsbUpKSq7Z3BxeXl7y8vJyaCtXrty9KtFofn5+/B8TxYJ7DcWFew3FhXut4G43Y5ujxD9Q5unpqaioKK1du9ahfe3atWrWrJmTqgIAAIAzlPiZW0l6/vnn9cQTT6hRo0Zq2rSp3n33XZ08eVLPPPOMs0sDAABAMTIi3Pbq1UupqamaOHGikpKSFBkZqc8//1yVK1d2dmnG8vLy0rhx43It7wCKGvcaigv3GooL99q9ZbPu9D4FAAAAoIQo8WtuAQAAgByEWwAAABiDcAsAAABjEG4BAABgDMItAAAAjEG4BQAAgDEItwAAADAG4Rb5lpqaqo0bN+r8+fOSpHPnzmnatGmaOHGijh496uTqYJorV65o7NixatasmWrUqKFq1ao5bEBROX36tC5fvpyr/fr169qyZYsTKsJvzY8//qiJEyc6uwxj8CUOyJddu3apbdu2Sk9PV7ly5bR27Vr96U9/kru7uyzL0pkzZ7Rt2zY1bNjQ2aXCEH369NHmzZv1xBNPqGLFirLZbA79w4cPd1JlMEVSUpK6du2qhIQE2Ww29evXT/PmzVPZsmUl/Rw4wsLClJ2d7eRKYboDBw6oYcOG3GtFhHCLfGnTpo2qVKmiGTNm6J133tHs2bP12GOP6b333pMkDRo0SKmpqYqPj3dypTBFuXLl9Nlnn6l58+bOLgWG6t+/v/73v/9pzpw5unjxokaPHi3LsrR27VoFBAToxx9/VMWKFXXz5k1nl4oS7uDBg7ft/+abb9SnTx/CbREh3CJfAgMD9eWXX6pWrVq6fv26vL29tWPHDv3+97+XJO3bt0+dO3fW6dOnnVwpTFG1alV9/vnnqlWrlrNLgaHuu+8+xcfH23+PZWZmqlevXvrhhx+0fv16Xb9+nZlbFIlSpUrJZrMpr8iV026z2bjXighrbpEvWVlZKl26tCTJw8NDPj4+Cg4OtvcHBQUpNTXVWeXBQJMmTdIrr7yiq1evOrsUGCotLU0BAQH2fS8vL3388ceqUqWKYmJilJKS4sTqYJKgoCC99957SkxMzLUdP35cn376qbNLNIq7swtAyRAeHq7jx4+rSpUqkqRly5apYsWK9v6kpCSHsAvcrTfeeEPff/+9QkJCVKVKFXl4eDj0792710mVwRTVqlXTwYMHFRERYW9zd3fX8uXL9ac//UmdOnVyYnUwSVRUlM6ePavKlSvn2X/x4sU8Z3VROIRb5Evv3r0dZjE6duzo0L9y5Ur7n/aAotCtWzdnlwDDtW/fXu+++6569Ojh0J4TcHv06MFSKxSJwYMH68qVK7fsr1SpkhYsWFCMFZmNNbcotJxbx2az6erVq3Jzc5OXl5eTqwKA/Llx44auXr0qPz8/e9svf69lZ2fr9OnTt5xtA+7GL+81FC3W3KLA3n//fUVGRsrb21ve3t6KjIzUkiVLCLYoUmPGjNHatWtZc4t7xt3d3R5s8/q9tmDBAoItilxe99o//vEPZ5dlFJYloEDGjh2rmTNnatiwYWratKkkaceOHRoxYoROnDihv//9706uEKZISEjQnDlzlJmZqYYNGyo6OlotW7bUww8/bH8PKVAU+L2G4sK9VjxYloACCQ4O1pw5c9SnTx+H9qVLl2rYsGE6d+6ckyqDibKzs7Vr1y5t3rxZmzZt0o4dO5SRkaGGDRtq586dzi4PhuD3GooL91rxYOYWBZKdna1GjRrlao+KitKNGzecUBFM5ubmpqZNmyowMFABAQHy9fXVihUr9P333zu7NBiE32soLtxrxYM1tyiQxx9/XPPnz8/V/u6776pfv35OqAimmj9/vnr37q2KFSuqRYsWWrNmjVq0aKGEhAT99NNPzi4PBuH3GooL91rxYFkCCmTYsGH68MMPFR4eroceekiStHPnTp06dUpPPvmkw7tIZ8yY4awyYYBSpUqpfPnyGjlypJ555hmHJ9qBosTvNRQX7rXiQbhFgcTExORrnM1m04YNG+5xNTDZihUrtGXLFm3atElff/216tWrp+joaEVHR6tFixY8VIYiw+81FBfuteJBuAXg8tLS0rR161Z9/PHHWrJkiWw2mzIzM51dFgDABfFAGQCXdf78efubEjZt2qTDhw8rKChILVu2dHZpAAAXxcwtAJdUt25dff311woMDNQjjzxiX5IQGRnp7NIAAC6MmVsALukvf/kLYRYAUGDM3AJweXwHOwAgv3jPLQCX9eGHH6pOnToqXbq0Spcurbp162rRokXOLgsA4MJYlgDAJc2YMUNjx47V0KFD1bx5c1mWpS+//FLPPPOMzp07pxEjRji7RACAC2JZAgCXVLVqVU2YMEFPPvmkQ/vChQs1fvx4JSYmOqkyAIArY1kCAJeUlJSkZs2a5Wpv1qyZkpKSnFARAKAkINwCcEk1atTQv/71r1ztH330kSIiIpxQEQCgJGDNLQCXNGHCBPXq1UtbtmxR8+bNZbPZtG3bNq1fvz7P0AsAgMSaWwAuLCEhQTNnztTRo0dlWZZq166tkSNHqkGDBs4uDQDgogi3AAAAMAbLEgC4rJs3b+rYsWNKSUnRzZs3HfoeeeQRJ1UFAHBlhFsALmnnzp3q27evfvjhB/36D0w2m03Z2dlOqgwA4MpYlgDAJdWvX1+/+93vNGHCBFWsWDHXV+/6+/s7qTIAgCsj3AJwSWXKlNGBAwdUo0YNZ5cCAChBeM8tAJfUpEkTHTt2zNllAABKGNbcAnBJw4YN08iRI5WcnKw6derIw8PDob9u3bpOqgwA4MpYlgDAJZUqlfsPSzabTZZl8UAZAOCWmLkF4JISExOdXQIAoAQi3AJwSf7+/ipXrlyefazFBQDcCg+UAXBJHTp00LVr13K1f/vtt4qOji7+ggAAJQLhFoBLCggIULdu3XTjxg1729GjRxUdHa0ePXo4sTIAgCsj3AJwSf/+97915coV9e3bV5Zl6fDhw4qOjlafPn00e/ZsZ5cHAHBRvC0BgMtKS0tTdHS0qlevrq1bt+rJJ5/Ua6+95uyyAAAujHALwGWkp6fnaktOTlbr1q3VqVMnTZ061d7u5+dXnKUBAEoIwi0Al1GqVCnZbLZc7Tm/pnjPLQDgTngVGACXsXHjRmeXAAAo4Zi5BQAAgDGYuQXgsi5evKhdu3YpJSVFN2/edOh78sknnVQVAMCVMXMLwCWtWrVK/fr105UrV+Tr6+uwFtdms+n8+fNOrA4A4KoItwBc0u9+9zt16NBBkydPlo+Pj7PLAQCUEIRbAC6pTJkyOnTokKpVq+bsUgAAJQjfUAbAJbVr10579uxxdhkAgBKGB8oAuKSOHTvqhRde0Ndff606derIw8PDob9Lly5OqgwA4MpYlgDAJZUqdes/LPElDgCAWyHcAgAAwBgsSwDgkiZOnHjLPpvNprFjxxZjNQCAkoKZWwAuqUGDBg77169fV2Jiotzd3VW9enXt3bvXSZUBAFwZM7cAXNK+fftytaWnp2vAgAH6wx/+4ISKAAAlATO3AEqUw4cPq1OnTjpx4oSzSwEAuCDecwugRLl48aLS0tKcXQYAwEWxLAGAS3rzzTcd9i3LUlJSkhYtWqTHHnvMSVUBAFwdyxIAuKSqVas67JcqVUrly5fXo48+qtGjR8vX19dJlQEAXBnhFgAAAMZgzS0AAACMQbgFAACAMQi3AAAAMAbhFgAAAMYg3AJACfTNN9/ooYcekre3t+rXr+/scu7K+PHjS/w1AHAdhFsA+JUBAwbIZrPJZrPJw8ND1apV06hRo3TlypW7Om5Rhrhx48apTJky+vbbb7V+/fo8x6SkpGjw4MGqVKmSvLy8FBoaqnbt2mnHjh1FUgMAuCK+xAEA8vDYY49pwYIFun79urZu3apBgwbpypUrmj9/foGPZVmWsrOzi7S+77//Xh07dlTlypVvOaZHjx66fv26Fi5cqGrVqunHH3/U+vXrdf78+SKtBQBcCTO3AJCHnJnO8PBw9e3bV/369dOKFSskSYsXL1ajRo3k6+ur0NBQ9e3bVykpKfbPbtq0STabTV988YUaNWokLy8vLVq0SBMmTNCBAwfss8JxcXF5nvvmzZuaOHGi7r//fnl5eal+/fpavXq1vd9msykhIUETJ06UzWbT+PHjcx3j4sWL2rZtm6ZNm6aYmBhVrlxZv//97zV69Gh17NjR4Vjz589X+/btVbp0aVWtWlXLly93ONaZM2fUq1cvBQQEKCgoSF27dtWJEyccxixYsEC1atWSt7e3HnjgAb311lsO/adPn1bv3r0VGBioMmXKqFGjRvrqq68cxixatEhVqlSRv7+/evfurUuXLt3qPw8A3BLhFgDyoXTp0rp+/bokKSsrS5MmTdKBAwe0YsUKJSYmasCAAbk+8+KLL2rKlCk6evSo2rZtq5EjR+rBBx9UUlKSkpKS1KtXrzzPNXv2bL3xxht6/fXXdfDgQbVr105dunTRd999J0lKSkrSgw8+qJEjRyopKUmjRo3KdYyyZcuqbNmyWrFihTIzM297bWPHjlWPHj104MABPf744+rTp4+OHj0qSbp69apiYmJUtmxZbdmyRdu2bVPZsmX12GOPKSsrS5L03nvvacyYMXr11Vd19OhRTZ48WWPHjtXChQslSZcvX1bLli119uxZrVy5UgcOHNCLL76omzdv2mv4/vvvtWLFCn366af69NNPtXnzZk2dOvUO/1UAIA8WAMBB//79ra5du9r3v/rqKysoKMjq2bNnnuN37dplSbIuXbpkWZZlbdy40ZJkrVixwmHcuHHjrHr16t3x/GFhYdarr77q0Na4cWNryJAh9v169epZ48aNu+1xPv74YysgIMDy9va2mjVrZo0ePdo6cOCAwxhJ1jPPPOPQ1qRJE+vZZ5+1LMuy3n//fatmzZrWzZs37f2ZmZlW6dKlrS+++MKyLMsKDw+3lixZ4nCMSZMmWU2bNrUsy7Leeecdy9fX10pNTc2zznHjxlk+Pj5Wenq6ve2FF16wmjRpctvrA4C8MHMLAHn49NNPVbZsWXl7e6tp06Z65JFHNGfOHEnSvn371LVrV1WuXFm+vr6Kjo6WJJ08edLhGI0aNSrwedPT03X27Fk1b97cob158+b22dT86tGjh322tF27dtq0aZMaNmyYazlE06ZNc+3nnCshIUHHjh2Tr6+vfTY4MDBQ165d0/fff6+ffvpJp06d0sCBA+39ZcuW1d///nd9//33kqT9+/erQYMGCgwMvGWtVapUka+vr32/YsWKDks9ACC/eKAMAPIQExOj+fPny8PDQ2FhYfLw8JAkXblyRW3btlXbtm21ePFilS9fXidPnlS7du3sf6bPUaZMmUKf32azOexblpWrLT+8vb3Vpk0btWnTRq+88ooGDRqkcePG5bmMIq/z37x5U1FRUfrnP/+Za0z58uV17do1ST8vTWjSpIlDv5ubm6Sfl3TcSc7P95fn/+WyBQDIL2ZuASAPZcqUUY0aNVS5cmWH4PXNN9/o3Llzmjp1qlq0aKEHHngg3zOMnp6ed3xrgp+fn8LCwrRt2zaH9u3bt6tWrVoFv5BfqV27dq5Xmu3cuTPX/gMPPCBJatiwob777jtVqFBBNWrUcNj8/f0VEhKi++67T8ePH8/VX7VqVUlS3bp1tX//ft7SAKBYEG4BoAAqVaokT09PzZkzR8ePH9fKlSs1adKkfH22SpUqSkxM1P79+3Xu3LlbPuj1wgsvaNq0afroo4/07bff6m9/+5v279+v4cOH57vO1NRUPfroo1q8eLEOHjyoxMRELV++XNOnT1fXrl0dxi5fvlwffPCB/ve//2ncuHHatWuXhg4dKknq16+fgoOD1bVrV23dulWJiYnavHmzhg8frtOnT0v6+f29U6ZM0ezZs/W///1Phw4d0oIFCzRjxgxJUp8+fRQaGqpu3brpyy+/1PHjx/Xvf/+b9+0CuCcItwBQAOXLl1dcXJyWL1+u2rVra+rUqXr99dfz9dkePXroscceU0xMjMqXL6+lS5fmOe6vf/2rRo4cqZEjR6pOnTpavXq1Vq5cqYiIiHzXWbZsWTVp0kQzZ87UI488osjISI0dO1Z//vOfNXfuXIexEyZM0LJly1S3bl0tXLhQ//znP1W7dm1Jko+Pj7Zs2aJKlSqpe/fuqlWrlp5++mllZGTIz89PkjRo0CD94x//UFxcnOrUqaOWLVsqLi7OPnPr6empNWvWqEKFCurQoYPq1KmjqVOn2pctAEBRslmWZTm7CACAc9hsNsXHx6tbt27OLgUAigQztwAAADAG4RYAAADG4FVgAPAbxso0AKZh5hYAAADGINwCAADAGIRbAAAAGINwCwAAAGMQbgEAAGAMwi0AAACMQbgFAACAMQi3AAAAMMb/A+NmU5gEOJi2AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tense_counts= BHSallVerbalMorphologyOTST551_sampled['bol_vt1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "tense_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "ps_counts= BHSallVerbalMorphologyOTST551_sampled['ps1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "ps_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall PS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "gn_counts= BHSallVerbalMorphologyOTST551_sampled['gn1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "gn_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall GN Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vc_counts= BHSallVerbalMorphologyOTST551_sampled['bol_dict_vc1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vc_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VC Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vs_counts= BHSallVerbalMorphologyOTST551_sampled['vs1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vs_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### OTST552 sampling: Using `sample`" ] }, { "cell_type": "code", "execution_count": 176, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/03/qlrw_2h92mgd4n9sls7f84lc0000gn/T/ipykernel_43836/166546048.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n", " BHSallVerbalMorphologyOTST552_sampled=BHSallVerbalMorphologyOTST551_552_625[\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 51797 entries, 1 to 71297\n", "Data columns (total 48 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0 51797 non-null int64 \n", " 1 R 51797 non-null int64 \n", " 2 S1 51797 non-null object\n", " 3 S2 51797 non-null int64 \n", " 4 S3 51797 non-null int64 \n", " 5 NODE1 51797 non-null int64 \n", " 6 TYPE1 51797 non-null object\n", " 7 TEXT1 51797 non-null object\n", " 8 bol_bhsa_word_order1 51797 non-null int64 \n", " 9 bol_dict_EN1 51797 non-null object\n", " 10 bol_dict_HebArm1 51797 non-null object\n", " 11 bol_dict_abc1 51797 non-null int64 \n", " 12 bol_dict_vc1 51797 non-null object\n", " 13 bol_lexeme_occurrences1 51797 non-null int64 \n", " 14 bol_monad_num1 51797 non-null int64 \n", " 15 bol_qere_presence1 51797 non-null int64 \n", " 16 bol_vt1 51797 non-null object\n", " 17 dagesh1 18695 non-null object\n", " 18 freq_lex1 51797 non-null int64 \n", " 19 freq_occ1 51797 non-null int64 \n", " 20 g_word_noaccent1 51797 non-null object\n", " 21 gn1 51797 non-null object\n", " 22 language1 51797 non-null object\n", " 23 lex1 51797 non-null object\n", " 24 nme1 44580 non-null object\n", " 25 nu1 51797 non-null object\n", " 26 number1 51797 non-null int64 \n", " 27 pdp1 51797 non-null object\n", " 28 pfm1 43857 non-null object\n", " 29 prs1 51797 non-null object\n", " 30 prs_gn1 51797 non-null object\n", " 31 prs_nu1 51797 non-null object\n", " 32 prs_ps1 51797 non-null object\n", " 33 ps1 51797 non-null object\n", " 34 rank_occ1 51797 non-null int64 \n", " 35 sp1 51797 non-null object\n", " 36 st1 11841 non-null object\n", " 37 uvf1 51797 non-null object\n", " 38 vbe1 15858 non-null object\n", " 39 vbs1 51797 non-null object\n", " 40 vs1 51797 non-null object\n", " 41 vt1 51797 non-null object\n", " 42 paragogicNun 51797 non-null bool \n", " 43 emphaticImpv 51797 non-null bool \n", " 44 Transposition 51797 non-null bool \n", " 45 WayCohortEnding 51797 non-null bool \n", " 46 PielPualHit_wo_DF_compLengthening 51797 non-null bool \n", " 47 PielPualHit_w_DoubleDoubling 51797 non-null bool \n", "dtypes: bool(6), int64(14), object(28)\n", "memory usage: 17.3+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST552_sampled=BHSallVerbalMorphologyOTST551_552_625[\n", " (BHSallVerbalMorphology['bol_lexeme_occurrences1'] > 99)\n", " ]\n", "BHSallVerbalMorphologyOTST552_sampled.info()" ] }, { "cell_type": "code", "execution_count": 177, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
252526Genesis19154wordתֵרָאֶ֖ה154qal: see; get to know; look at; choose; ni: be...ראה7095i-guttural, ii-guttural, iii-hey12981540impfNaN129836T;R@>EHfHebrewR>H[absentsg154verbT=absentunknownunknownunknownp31075verbNaNabsentNaNNnifimpfFalseFalseFalseFalseFalseFalse
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
143143144Genesis215961wordשָׁמְרָֽהּ׃961qal: keep watch, guard; ni: be guarded; beware...שׁמר7869iii-guttural4689610infcNaN46810C@M:R@H.unknownHebrewCMR[NaNunknown961verbNaNHfsgp3unknown3149verbaabsentNaNabsentqalinfcFalseFalseFalseFalseFalseFalse
151151152Genesis217995wordתָּמֽוּת׃995qal: die; pi: kill; hi: kill, put to death; ho...מות4054ii-waw8359950impfDL_DF83534T.@MW.TmHebrewMWT[absentsg995verbTabsentunknownunknownunknownp21123verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "25 25 26 Genesis 1 9 154 word תֵרָאֶ֖ה \n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "143 143 144 Genesis 2 15 961 word שָׁמְרָֽהּ׃ \n", "151 151 152 Genesis 2 17 995 word תָּמֽוּת׃ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "25 154 qal: see; get to know; look at; choose; ni: be... \n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "143 961 qal: keep watch, guard; ni: be guarded; beware... \n", "151 995 qal: die; pi: kill; hi: kill, put to death; ho... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "25 ראה 7095 i-guttural, ii-guttural, iii-hey \n", "36 יצא 3207 i-waw, iii-aleph \n", "36 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "107 כלה 3494 iii-hey \n", "107 כלה 3494 iii-hey \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "143 שׁמר 7869 iii-guttural \n", "151 מות 4054 ii-waw \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "25 1298 154 0 impf \n", "36 1068 205 0 wayq \n", "36 1068 205 0 wayq \n", "76 1068 449 0 impf \n", "76 1068 449 0 impf \n", "107 206 675 0 wayq \n", "107 206 675 0 wayq \n", "141 141 953 0 wayq \n", "143 468 961 0 infc \n", "151 835 995 0 impf \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "25 NaN 1298 36 T;R@>EH f Hebrew R>H[ \n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "143 NaN 468 10 C@M:R@H. unknown Hebrew CMR[ \n", "151 DL_DF 835 34 T.@MW.T m Hebrew MWT[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 \\\n", "25 absent sg 154 verb T= absent unknown unknown unknown \n", "36 absent sg 205 verb T= absent unknown unknown unknown \n", "36 absent sg 205 verb T= absent unknown unknown unknown \n", "76 absent sg 449 verb T= absent unknown unknown unknown \n", "76 absent sg 449 verb T= absent unknown unknown unknown \n", "107 absent pl 675 verb J absent unknown unknown unknown \n", "107 absent pl 675 verb J absent unknown unknown unknown \n", "141 absent sg 953 verb J HW m sg p3 \n", "143 NaN unknown 961 verb NaN H f sg p3 \n", "151 absent sg 995 verb T absent unknown unknown unknown \n", "\n", " ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 \\\n", "25 p3 1075 verb NaN absent NaN N nif impf \n", "36 p3 7211 verb NaN absent NaN H hif wayq \n", "36 p3 7211 verb NaN absent NaN H hif wayq \n", "76 p3 7211 verb NaN absent NaN H hif impf \n", "76 p3 7211 verb NaN absent NaN H hif impf \n", "107 p3 781 verb NaN absent W absent pual wayq \n", "107 p3 781 verb NaN absent W absent pual wayq \n", "141 p3 7211 verb NaN absent NaN H hif wayq \n", "143 unknown 3149 verb a absent NaN absent qal infc \n", "151 p2 1123 verb NaN absent NaN absent qal impf \n", "\n", " paragogicNun emphaticImpv Transposition WayCohortEnding \\\n", "25 False False False False \n", "36 False False False False \n", "36 False False False False \n", "76 False False False False \n", "76 False False False False \n", "107 False False False False \n", "107 False False False False \n", "141 False False False False \n", "143 False False False False \n", "151 False False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "25 False False \n", "36 False False \n", "36 False False \n", "76 False False \n", "76 False False \n", "107 False False \n", "107 False False \n", "141 False False \n", "143 False False \n", "151 False False " ] }, "execution_count": 177, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHSallVerbalMorphologyOTST552_sampled=BHSallVerbalMorphologyOTST552_sampled \\\n", " .groupby(['ps1',\n", " 'gn1',\n", " 'nu1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'bol_dict_vc1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1']) \\\n", " .sample(n=2, random_state=1, replace=True)\\\n", " .sort_values(['bol_monad_num1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1'], \n", " ascending=True)\n", "BHSallVerbalMorphologyOTST552_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": 178, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
252526Genesis19154wordתֵרָאֶ֖ה154qal: see; get to know; look at; choose; ni: be...ראה7095i-guttural, ii-guttural, iii-hey12981540impfNaN129836T;R@>EHfHebrewR>H[absentsg154verbT=absentunknownunknownunknownp31075verbNaNabsentNaNNnifimpfFalseFalseFalseFalseFalseFalse
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "25 25 26 Genesis 1 9 154 word תֵרָאֶ֖ה \n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "25 154 qal: see; get to know; look at; choose; ni: be... \n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "25 ראה 7095 i-guttural, ii-guttural, iii-hey \n", "36 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "107 כלה 3494 iii-hey \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "25 1298 154 0 impf \n", "36 1068 205 0 wayq \n", "76 1068 449 0 impf \n", "107 206 675 0 wayq \n", "141 141 953 0 wayq \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "25 NaN 1298 36 T;R@>EH f Hebrew R>H[ \n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 \\\n", "25 absent sg 154 verb T= absent unknown unknown unknown p3 \n", "36 absent sg 205 verb T= absent unknown unknown unknown p3 \n", "76 absent sg 449 verb T= absent unknown unknown unknown p3 \n", "107 absent pl 675 verb J absent unknown unknown unknown p3 \n", "141 absent sg 953 verb J HW m sg p3 p3 \n", "\n", " rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "25 1075 verb NaN absent NaN N nif impf False \n", "36 7211 verb NaN absent NaN H hif wayq False \n", "76 7211 verb NaN absent NaN H hif impf False \n", "107 781 verb NaN absent W absent pual wayq False \n", "141 7211 verb NaN absent NaN H hif wayq False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "25 False False False \n", "36 False False False \n", "76 False False False \n", "107 False False False \n", "141 False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "25 False False \n", "36 False False \n", "76 False False \n", "107 False False \n", "141 False False " ] }, "execution_count": 178, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST552_sampled.drop_duplicates(subset=\"bol_monad_num1\", keep='first', inplace=True)\n", "BHSallVerbalMorphologyOTST552_sampled.head(5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST552 raw sampled data" ] }, { "cell_type": "code", "execution_count": 179, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
252526Genesis19154wordתֵרָאֶ֖ה154qal: see; get to know; look at; choose; ni: be...ראה7095i-guttural, ii-guttural, iii-hey12981540impfNaN129836T;R@>EHfHebrewR>H[absentsg154verbT=absentunknownunknownunknownp31075verbNaNabsentNaNNnifimpfFalseFalseFalseFalseFalseFalse
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "25 25 26 Genesis 1 9 154 word תֵרָאֶ֖ה \n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "25 154 qal: see; get to know; look at; choose; ni: be... \n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "25 ראה 7095 i-guttural, ii-guttural, iii-hey \n", "36 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "107 כלה 3494 iii-hey \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "25 1298 154 0 impf \n", "36 1068 205 0 wayq \n", "76 1068 449 0 impf \n", "107 206 675 0 wayq \n", "141 141 953 0 wayq \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "25 NaN 1298 36 T;R@>EH f Hebrew R>H[ \n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 \\\n", "25 absent sg 154 verb T= absent unknown unknown unknown p3 \n", "36 absent sg 205 verb T= absent unknown unknown unknown p3 \n", "76 absent sg 449 verb T= absent unknown unknown unknown p3 \n", "107 absent pl 675 verb J absent unknown unknown unknown p3 \n", "141 absent sg 953 verb J HW m sg p3 p3 \n", "\n", " rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "25 1075 verb NaN absent NaN N nif impf False \n", "36 7211 verb NaN absent NaN H hif wayq False \n", "76 7211 verb NaN absent NaN H hif impf False \n", "107 781 verb NaN absent W absent pual wayq False \n", "141 7211 verb NaN absent NaN H hif wayq False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "25 False False False \n", "36 False False False \n", "76 False False False \n", "107 False False False \n", "141 False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "25 False False \n", "36 False False \n", "76 False False \n", "107 False False \n", "141 False False " ] }, "execution_count": 179, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST552_sampled.head()" ] }, { "cell_type": "code", "execution_count": 180, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tense_counts= BHSallVerbalMorphologyOTST552_sampled['bol_vt1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "tense_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "ps_counts= BHSallVerbalMorphologyOTST552_sampled['ps1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "ps_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall PS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "gn_counts= BHSallVerbalMorphologyOTST552_sampled['gn1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "gn_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall GN Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vc_counts= BHSallVerbalMorphologyOTST552_sampled['bol_dict_vc1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vc_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VC Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vs_counts= BHSallVerbalMorphologyOTST552_sampled['vs1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vs_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### OTST625 sampling: Using `sample`" ] }, { "cell_type": "code", "execution_count": 181, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/03/qlrw_2h92mgd4n9sls7f84lc0000gn/T/ipykernel_43836/1253110721.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n", " BHSallVerbalMorphologyOTST625_sampled=BHSallVerbalMorphologyOTST551_552_625[\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 55259 entries, 1 to 71297\n", "Data columns (total 48 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0 55259 non-null int64 \n", " 1 R 55259 non-null int64 \n", " 2 S1 55259 non-null object\n", " 3 S2 55259 non-null int64 \n", " 4 S3 55259 non-null int64 \n", " 5 NODE1 55259 non-null int64 \n", " 6 TYPE1 55259 non-null object\n", " 7 TEXT1 55259 non-null object\n", " 8 bol_bhsa_word_order1 55259 non-null int64 \n", " 9 bol_dict_EN1 55259 non-null object\n", " 10 bol_dict_HebArm1 55259 non-null object\n", " 11 bol_dict_abc1 55259 non-null int64 \n", " 12 bol_dict_vc1 55259 non-null object\n", " 13 bol_lexeme_occurrences1 55259 non-null int64 \n", " 14 bol_monad_num1 55259 non-null int64 \n", " 15 bol_qere_presence1 55259 non-null int64 \n", " 16 bol_vt1 55259 non-null object\n", " 17 dagesh1 19868 non-null object\n", " 18 freq_lex1 55259 non-null int64 \n", " 19 freq_occ1 55259 non-null int64 \n", " 20 g_word_noaccent1 55259 non-null object\n", " 21 gn1 55259 non-null object\n", " 22 language1 55259 non-null object\n", " 23 lex1 55259 non-null object\n", " 24 nme1 47555 non-null object\n", " 25 nu1 55259 non-null object\n", " 26 number1 55259 non-null int64 \n", " 27 pdp1 55259 non-null object\n", " 28 pfm1 46809 non-null object\n", " 29 prs1 55259 non-null object\n", " 30 prs_gn1 55259 non-null object\n", " 31 prs_nu1 55259 non-null object\n", " 32 prs_ps1 55259 non-null object\n", " 33 ps1 55259 non-null object\n", " 34 rank_occ1 55259 non-null int64 \n", " 35 sp1 55259 non-null object\n", " 36 st1 12656 non-null object\n", " 37 uvf1 55259 non-null object\n", " 38 vbe1 16896 non-null object\n", " 39 vbs1 55259 non-null object\n", " 40 vs1 55259 non-null object\n", " 41 vt1 55259 non-null object\n", " 42 paragogicNun 55259 non-null bool \n", " 43 emphaticImpv 55259 non-null bool \n", " 44 Transposition 55259 non-null bool \n", " 45 WayCohortEnding 55259 non-null bool \n", " 46 PielPualHit_wo_DF_compLengthening 55259 non-null bool \n", " 47 PielPualHit_w_DoubleDoubling 55259 non-null bool \n", "dtypes: bool(6), int64(14), object(28)\n", "memory usage: 18.4+ MB\n" ] } ], "source": [ "BHSallVerbalMorphologyOTST625_sampled=BHSallVerbalMorphologyOTST551_552_625[\n", " (BHSallVerbalMorphology['bol_lexeme_occurrences1'] >= 70)\n", " ]\n", "BHSallVerbalMorphologyOTST625_sampled.info()" ] }, { "cell_type": "code", "execution_count": 182, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
143143144Genesis215961wordשָׁמְרָֽהּ׃961qal: keep watch, guard; ni: be guarded; beware...שׁמר7869iii-guttural4689610infcNaN46810C@M:R@H.unknownHebrewCMR[NaNunknown961verbNaNHfsgp3unknown3149verbaabsentNaNabsentqalinfcFalseFalseFalseFalseFalseFalse
147147148Genesis216977wordתֹּאכֵֽל׃977qal: eat, devour; qal pass: eat; ni: be eaten;...אכל383i-aleph8109770impfDL81089T.O>K;LmHebrew>KL[absentsg977verbTabsentunknownunknownunknownp2466verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
150150151Genesis217994wordמֹ֥ות994qal: die; pi: kill; hi: kill, put to death; ho...מות4054ii-waw8359940infaNaN835199MOWTunknownHebrewMWT[NaNunknown994advbNaNabsentunknownunknownunknownunknown217verbaabsentNaNabsentqalinfaFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "143 143 144 Genesis 2 15 961 word שָׁמְרָֽהּ׃ \n", "147 147 148 Genesis 2 16 977 word תֹּאכֵֽל׃ \n", "150 150 151 Genesis 2 17 994 word מֹ֥ות \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "143 961 qal: keep watch, guard; ni: be guarded; beware... \n", "147 977 qal: eat, devour; qal pass: eat; ni: be eaten;... \n", "150 994 qal: die; pi: kill; hi: kill, put to death; ho... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "36 יצא 3207 i-waw, iii-aleph \n", "36 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "107 כלה 3494 iii-hey \n", "107 כלה 3494 iii-hey \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "143 שׁמר 7869 iii-guttural \n", "147 אכל 383 i-aleph \n", "150 מות 4054 ii-waw \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "36 1068 205 0 wayq \n", "36 1068 205 0 wayq \n", "76 1068 449 0 impf \n", "107 206 675 0 wayq \n", "107 206 675 0 wayq \n", "141 141 953 0 wayq \n", "141 141 953 0 wayq \n", "143 468 961 0 infc \n", "147 810 977 0 impf \n", "150 835 994 0 infa \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "143 NaN 468 10 C@M:R@H. unknown Hebrew CMR[ \n", "147 DL 810 89 T.O>K;L m Hebrew >KL[ \n", "150 NaN 835 199 MOWT unknown Hebrew MWT[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 \\\n", "36 absent sg 205 verb T= absent unknown unknown unknown \n", "36 absent sg 205 verb T= absent unknown unknown unknown \n", "76 absent sg 449 verb T= absent unknown unknown unknown \n", "107 absent pl 675 verb J absent unknown unknown unknown \n", "107 absent pl 675 verb J absent unknown unknown unknown \n", "141 absent sg 953 verb J HW m sg p3 \n", "141 absent sg 953 verb J HW m sg p3 \n", "143 NaN unknown 961 verb NaN H f sg p3 \n", "147 absent sg 977 verb T absent unknown unknown unknown \n", "150 NaN unknown 994 advb NaN absent unknown unknown unknown \n", "\n", " ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 \\\n", "36 p3 7211 verb NaN absent NaN H hif wayq \n", "36 p3 7211 verb NaN absent NaN H hif wayq \n", "76 p3 7211 verb NaN absent NaN H hif impf \n", "107 p3 781 verb NaN absent W absent pual wayq \n", "107 p3 781 verb NaN absent W absent pual wayq \n", "141 p3 7211 verb NaN absent NaN H hif wayq \n", "141 p3 7211 verb NaN absent NaN H hif wayq \n", "143 unknown 3149 verb a absent NaN absent qal infc \n", "147 p2 466 verb NaN absent NaN absent qal impf \n", "150 unknown 217 verb a absent NaN absent qal infa \n", "\n", " paragogicNun emphaticImpv Transposition WayCohortEnding \\\n", "36 False False False False \n", "36 False False False False \n", "76 False False False False \n", "107 False False False False \n", "107 False False False False \n", "141 False False False False \n", "141 False False False False \n", "143 False False False False \n", "147 False False False False \n", "150 False False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "36 False False \n", "36 False False \n", "76 False False \n", "107 False False \n", "107 False False \n", "141 False False \n", "141 False False \n", "143 False False \n", "147 False False \n", "150 False False " ] }, "execution_count": 182, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHSallVerbalMorphologyOTST625_sampled=BHSallVerbalMorphologyOTST625_sampled \\\n", " .groupby(['ps1',\n", " 'gn1',\n", " 'nu1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'bol_dict_vc1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1']) \\\n", " .sample(n=2, random_state=1, replace=True)\\\n", " .sort_values(['bol_monad_num1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1'], \n", " ascending=True)\n", "BHSallVerbalMorphologyOTST625_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": 183, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
143143144Genesis215961wordשָׁמְרָֽהּ׃961qal: keep watch, guard; ni: be guarded; beware...שׁמר7869iii-guttural4689610infcNaN46810C@M:R@H.unknownHebrewCMR[NaNunknown961verbNaNHfsgp3unknown3149verbaabsentNaNabsentqalinfcFalseFalseFalseFalseFalseFalse
147147148Genesis216977wordתֹּאכֵֽל׃977qal: eat, devour; qal pass: eat; ni: be eaten;...אכל383i-aleph8109770impfDL81089T.O>K;LmHebrew>KL[absentsg977verbTabsentunknownunknownunknownp2466verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
150150151Genesis217994wordמֹ֥ות994qal: die; pi: kill; hi: kill, put to death; ho...מות4054ii-waw8359940infaNaN835199MOWTunknownHebrewMWT[NaNunknown994advbNaNabsentunknownunknownunknownunknown217verbaabsentNaNabsentqalinfaFalseFalseFalseFalseFalseFalse
168168169Genesis2221112wordיְבִאֶ֖הָ1112qal: come, enter, go in; hi: bring; let come; ...בוא889ii-waw, iii-aleph257011120wayqNaN25702J:BI>EH@mHebrewBW>[absentsg1112verbJHfsgp3p39178verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
171171172Genesis2231137wordלֻֽקֳחָה־1137qal: take, grasp, seize; qal pass: take, grasp...לקח3831i-nun, iii-guttural96511370perfNaN96511LUQ:@X@HfHebrewLQX[absentsg1137verbabsentabsentunknownunknownunknownp32952verbNaNabsentHabsentpualperfFalseFalseFalseFalseFalseFalse
183183184Genesis321210wordנֹאכֵֽל׃1210qal: eat, devour; qal pass: eat; ni: be eaten;...אכל383i-aleph81012100impfNaN8106NO>K;LunknownHebrew>KL[absentpl1210verbNabsentunknownunknownunknownp14554verbNaNabsentNaNabsentqalimpfFalseFalseFalseFalseFalseFalse
187187188Genesis331231wordתְּמֻתֽוּן׃1231qal: die; pi: kill; hi: kill, put to death; ho...מות4054ii-waw83512310impfDL_DF8353T.:MUTW.NmHebrewMWT[absentpl1231verbTabsentunknownunknownunknownp27211verbNaNabsentWNabsentqalimpfTrueFalseFalseFalseFalseFalse
195195196Genesis351257wordיֹדְעֵ֖י1257qal: know; notice; learn; ni: make oneself kno...ידע2947i-waw, iii-guttural94412570ptcaNaN94410JOD:<;JmHebrewJD<[Jpl1257subsabsentabsentunknownunknownunknownunknown3149verbcabsentNaNabsentqalptcaFalseFalseFalseFalseFalseFalse
208208209Genesis381321wordמִתְהַלֵּ֥ךְ1321qal: go, walk; ni: be gone, fade; pi: go, walk...הלך1879i-waw154713210ptcaNaN15478MIT:HAL.;K:mHebrewHLK[NaNsg1321verbMabsentunknownunknownunknownunknown3705verbaabsentNaNHThitptcaFalseFalseFalseFalseFalseFalse
214214215Genesis3101364wordאִירָ֛א1364qal: fear, be afraid; ni: be fearful, be terri...ירא3253i-waw, ii-guttural, iii-aleph33213640wayqNaN33212>IJR@>unknownHebrewJR>[absentsg1364verb>absentunknownunknownunknownp12761verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
229229230Genesis3131424wordאֹכֵֽל׃1424qal: eat, devour; qal pass: eat; ni: be eaten;...אכל383i-aleph81014240wayqNaN810164>OK;LunknownHebrew>KL[absentsg1424verb>absentunknownunknownunknownp1269verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
240240241Genesis3161482wordאַרְבֶּה֙1482qal: be numerous, become numerous, be great; p...רבה I7129i-guttural, iii-hey22414820impf_DL22433>AR:B.EHunknownHebrewRBH[absentsg1482verb>absentunknownunknownunknownp11153verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
245245246Genesis3171508wordתֹּ֨אכַל֙1508qal: eat, devour; qal pass: eat; ni: be eaten;...אכל383i-aleph81015080wayqDL81089T.O>KALmHebrew>KL[absentsg1508verbTabsentunknownunknownunknownp2466verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
246246247Genesis3171513wordצִוִּיתִ֨יךָ֙1513pi: command; pu: be ordered;צוה6557iii-hey49415130perfNaN4949YIW.IJTIJK@unknownHebrewYWH[absentsg1513verbabsentKmsgp2p13421verbNaNabsentTJabsentpielperfFalseFalseFalseFalseFalseFalse
254254255Genesis3191548wordשֽׁוּבְךָ֙1548qal: turn, return, repeat; pi: bring back; sed...שׁוב I7576ii-waw103715480infcNaN10384CW.B:K@unknownHebrewCWB[NaNunknown1548verbNaNKmsgp2unknown6060verbaabsentNaNabsentqalinfcFalseFalseFalseFalseFalseFalse
255255256Genesis3191554wordלֻקָּ֑חְתָּ1554qal: take, grasp, seize; qal pass: take, grasp...לקח3831i-nun, iii-guttural96515540perf_DL96547LUQ.@X:T.@mHebrewLQX[absentsg1554verbabsentabsentunknownunknownunknownp2838verbNaNabsentTabsentpualperfFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "143 143 144 Genesis 2 15 961 word שָׁמְרָֽהּ׃ \n", "147 147 148 Genesis 2 16 977 word תֹּאכֵֽל׃ \n", "150 150 151 Genesis 2 17 994 word מֹ֥ות \n", "168 168 169 Genesis 2 22 1112 word יְבִאֶ֖הָ \n", "171 171 172 Genesis 2 23 1137 word לֻֽקֳחָה־ \n", "183 183 184 Genesis 3 2 1210 word נֹאכֵֽל׃ \n", "187 187 188 Genesis 3 3 1231 word תְּמֻתֽוּן׃ \n", "195 195 196 Genesis 3 5 1257 word יֹדְעֵ֖י \n", "208 208 209 Genesis 3 8 1321 word מִתְהַלֵּ֥ךְ \n", "214 214 215 Genesis 3 10 1364 word אִירָ֛א \n", "229 229 230 Genesis 3 13 1424 word אֹכֵֽל׃ \n", "240 240 241 Genesis 3 16 1482 word אַרְבֶּה֙ \n", "245 245 246 Genesis 3 17 1508 word תֹּ֨אכַל֙ \n", "246 246 247 Genesis 3 17 1513 word צִוִּיתִ֨יךָ֙ \n", "254 254 255 Genesis 3 19 1548 word שֽׁוּבְךָ֙ \n", "255 255 256 Genesis 3 19 1554 word לֻקָּ֑חְתָּ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "143 961 qal: keep watch, guard; ni: be guarded; beware... \n", "147 977 qal: eat, devour; qal pass: eat; ni: be eaten;... \n", "150 994 qal: die; pi: kill; hi: kill, put to death; ho... \n", "168 1112 qal: come, enter, go in; hi: bring; let come; ... \n", "171 1137 qal: take, grasp, seize; qal pass: take, grasp... \n", "183 1210 qal: eat, devour; qal pass: eat; ni: be eaten;... \n", "187 1231 qal: die; pi: kill; hi: kill, put to death; ho... \n", "195 1257 qal: know; notice; learn; ni: make oneself kno... \n", "208 1321 qal: go, walk; ni: be gone, fade; pi: go, walk... \n", "214 1364 qal: fear, be afraid; ni: be fearful, be terri... \n", "229 1424 qal: eat, devour; qal pass: eat; ni: be eaten;... \n", "240 1482 qal: be numerous, become numerous, be great; p... \n", "245 1508 qal: eat, devour; qal pass: eat; ni: be eaten;... \n", "246 1513 pi: command; pu: be ordered; \n", "254 1548 qal: turn, return, repeat; pi: bring back; sed... \n", "255 1554 qal: take, grasp, seize; qal pass: take, grasp... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "36 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "107 כלה 3494 iii-hey \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "143 שׁמר 7869 iii-guttural \n", "147 אכל 383 i-aleph \n", "150 מות 4054 ii-waw \n", "168 בוא 889 ii-waw, iii-aleph \n", "171 לקח 3831 i-nun, iii-guttural \n", "183 אכל 383 i-aleph \n", "187 מות 4054 ii-waw \n", "195 ידע 2947 i-waw, iii-guttural \n", "208 הלך 1879 i-waw \n", "214 ירא 3253 i-waw, ii-guttural, iii-aleph \n", "229 אכל 383 i-aleph \n", "240 רבה I 7129 i-guttural, iii-hey \n", "245 אכל 383 i-aleph \n", "246 צוה 6557 iii-hey \n", "254 שׁוב I 7576 ii-waw \n", "255 לקח 3831 i-nun, iii-guttural \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "36 1068 205 0 wayq \n", "76 1068 449 0 impf \n", "107 206 675 0 wayq \n", "141 141 953 0 wayq \n", "143 468 961 0 infc \n", "147 810 977 0 impf \n", "150 835 994 0 infa \n", "168 2570 1112 0 wayq \n", "171 965 1137 0 perf \n", "183 810 1210 0 impf \n", "187 835 1231 0 impf \n", "195 944 1257 0 ptca \n", "208 1547 1321 0 ptca \n", "214 332 1364 0 wayq \n", "229 810 1424 0 wayq \n", "240 224 1482 0 impf \n", "245 810 1508 0 wayq \n", "246 494 1513 0 perf \n", "254 1037 1548 0 infc \n", "255 965 1554 0 perf \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "143 NaN 468 10 C@M:R@H. unknown Hebrew CMR[ \n", "147 DL 810 89 T.O>K;L m Hebrew >KL[ \n", "150 NaN 835 199 MOWT unknown Hebrew MWT[ \n", "168 NaN 2570 2 J:BI>EH@ m Hebrew BW>[ \n", "171 NaN 965 11 LUQ:@X@H f Hebrew LQX[ \n", "183 NaN 810 6 NO>K;L unknown Hebrew >KL[ \n", "187 DL_DF 835 3 T.:MUTW.N m Hebrew MWT[ \n", "195 NaN 944 10 JOD:<;J m Hebrew JD<[ \n", "208 NaN 1547 8 MIT:HAL.;K: m Hebrew HLK[ \n", "214 NaN 332 12 >IJR@> unknown Hebrew JR>[ \n", "229 NaN 810 164 >OK;L unknown Hebrew >KL[ \n", "240 _DL 224 33 >AR:B.EH unknown Hebrew RBH[ \n", "245 DL 810 89 T.O>KAL m Hebrew >KL[ \n", "246 NaN 494 9 YIW.IJTIJK@ unknown Hebrew YWH[ \n", "254 NaN 1038 4 CW.B:K@ unknown Hebrew CWB[ \n", "255 _DL 965 47 LUQ.@X:T.@ m Hebrew LQX[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 \\\n", "36 absent sg 205 verb T= absent unknown unknown \n", "76 absent sg 449 verb T= absent unknown unknown \n", "107 absent pl 675 verb J absent unknown unknown \n", "141 absent sg 953 verb J HW m sg \n", "143 NaN unknown 961 verb NaN H f sg \n", "147 absent sg 977 verb T absent unknown unknown \n", "150 NaN unknown 994 advb NaN absent unknown unknown \n", "168 absent sg 1112 verb J H f sg \n", "171 absent sg 1137 verb absent absent unknown unknown \n", "183 absent pl 1210 verb N absent unknown unknown \n", "187 absent pl 1231 verb T absent unknown unknown \n", "195 J pl 1257 subs absent absent unknown unknown \n", "208 NaN sg 1321 verb M absent unknown unknown \n", "214 absent sg 1364 verb > absent unknown unknown \n", "229 absent sg 1424 verb > absent unknown unknown \n", "240 absent sg 1482 verb > absent unknown unknown \n", "245 absent sg 1508 verb T absent unknown unknown \n", "246 absent sg 1513 verb absent K m sg \n", "254 NaN unknown 1548 verb NaN K m sg \n", "255 absent sg 1554 verb absent absent unknown unknown \n", "\n", " prs_ps1 ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 \\\n", "36 unknown p3 7211 verb NaN absent NaN H hif wayq \n", "76 unknown p3 7211 verb NaN absent NaN H hif impf \n", "107 unknown p3 781 verb NaN absent W absent pual wayq \n", "141 p3 p3 7211 verb NaN absent NaN H hif wayq \n", "143 p3 unknown 3149 verb a absent NaN absent qal infc \n", "147 unknown p2 466 verb NaN absent NaN absent qal impf \n", "150 unknown unknown 217 verb a absent NaN absent qal infa \n", "168 p3 p3 9178 verb NaN absent NaN H hif wayq \n", "171 unknown p3 2952 verb NaN absent H absent pual perf \n", "183 unknown p1 4554 verb NaN absent NaN absent qal impf \n", "187 unknown p2 7211 verb NaN absent WN absent qal impf \n", "195 unknown unknown 3149 verb c absent NaN absent qal ptca \n", "208 unknown unknown 3705 verb a absent NaN HT hit ptca \n", "214 unknown p1 2761 verb NaN absent NaN absent qal wayq \n", "229 unknown p1 269 verb NaN absent NaN absent qal wayq \n", "240 unknown p1 1153 verb NaN absent NaN H hif impf \n", "245 unknown p2 466 verb NaN absent NaN absent qal wayq \n", "246 p2 p1 3421 verb NaN absent TJ absent piel perf \n", "254 p2 unknown 6060 verb a absent NaN absent qal infc \n", "255 unknown p2 838 verb NaN absent T absent pual perf \n", "\n", " paragogicNun emphaticImpv Transposition WayCohortEnding \\\n", "36 False False False False \n", "76 False False False False \n", "107 False False False False \n", "141 False False False False \n", "143 False False False False \n", "147 False False False False \n", "150 False False False False \n", "168 False False False False \n", "171 False False False False \n", "183 False False False False \n", "187 True False False False \n", "195 False False False False \n", "208 False False False False \n", "214 False False False False \n", "229 False False False False \n", "240 False False False False \n", "245 False False False False \n", "246 False False False False \n", "254 False False False False \n", "255 False False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "36 False False \n", "76 False False \n", "107 False False \n", "141 False False \n", "143 False False \n", "147 False False \n", "150 False False \n", "168 False False \n", "171 False False \n", "183 False False \n", "187 False False \n", "195 False False \n", "208 False False \n", "214 False False \n", "229 False False \n", "240 False False \n", "245 False False \n", "246 False False \n", "254 False False \n", "255 False False " ] }, "execution_count": 183, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST625_sampled.drop_duplicates(subset=\"bol_monad_num1\", keep='first', inplace=True)\n", "BHSallVerbalMorphologyOTST625_sampled.head(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST625 raw sampled data" ] }, { "cell_type": "code", "execution_count": 184, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
363637Genesis112205wordתֹּוצֵ֨א205qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10682050wayqDL10683T.OWY;>fHebrewJY>[absentsg205verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
767677Genesis124449wordתֹּוצֵ֨א449qal: go out, go forth; hi: bring; ho: be broug...יצא3207i-waw, iii-aleph10684490impfDL10683T.OWY;>fHebrewJY>[absentsg449verbT=absentunknownunknownunknownp37211verbNaNabsentNaNHhifimpfFalseFalseFalseFalseFalseFalse
107107108Genesis21675wordיְכֻלּ֛וּ675qal: come to an end, be completed, long for; p...כלה3494iii-hey2066750wayqNaN20651J:KUL.W.mHebrewKLH[absentpl675verbJabsentunknownunknownunknownp3781verbNaNabsentWabsentpualwayqFalseFalseFalseFalseFalseFalse
141141142Genesis215953wordיַּנִּחֵ֣הוּ953qal: rest, settle down, make quiet; hi: lay, d...נוח I4989i-nun, ii-waw, iii-guttural1419530wayqDF_DF1413J.AN.IX;HW.mHebrewNWX[absentsg953verbJHWmsgp3p37211verbNaNabsentNaNHhifwayqFalseFalseFalseFalseFalseFalse
143143144Genesis215961wordשָׁמְרָֽהּ׃961qal: keep watch, guard; ni: be guarded; beware...שׁמר7869iii-guttural4689610infcNaN46810C@M:R@H.unknownHebrewCMR[NaNunknown961verbNaNHfsgp3unknown3149verbaabsentNaNabsentqalinfcFalseFalseFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 TEXT1 \\\n", "36 36 37 Genesis 1 12 205 word תֹּוצֵ֨א \n", "76 76 77 Genesis 1 24 449 word תֹּוצֵ֨א \n", "107 107 108 Genesis 2 1 675 word יְכֻלּ֛וּ \n", "141 141 142 Genesis 2 15 953 word יַּנִּחֵ֣הוּ \n", "143 143 144 Genesis 2 15 961 word שָׁמְרָֽהּ׃ \n", "\n", " bol_bhsa_word_order1 bol_dict_EN1 \\\n", "36 205 qal: go out, go forth; hi: bring; ho: be broug... \n", "76 449 qal: go out, go forth; hi: bring; ho: be broug... \n", "107 675 qal: come to an end, be completed, long for; p... \n", "141 953 qal: rest, settle down, make quiet; hi: lay, d... \n", "143 961 qal: keep watch, guard; ni: be guarded; beware... \n", "\n", " bol_dict_HebArm1 bol_dict_abc1 bol_dict_vc1 \\\n", "36 יצא 3207 i-waw, iii-aleph \n", "76 יצא 3207 i-waw, iii-aleph \n", "107 כלה 3494 iii-hey \n", "141 נוח I 4989 i-nun, ii-waw, iii-guttural \n", "143 שׁמר 7869 iii-guttural \n", "\n", " bol_lexeme_occurrences1 bol_monad_num1 bol_qere_presence1 bol_vt1 \\\n", "36 1068 205 0 wayq \n", "76 1068 449 0 impf \n", "107 206 675 0 wayq \n", "141 141 953 0 wayq \n", "143 468 961 0 infc \n", "\n", " dagesh1 freq_lex1 freq_occ1 g_word_noaccent1 gn1 language1 lex1 \\\n", "36 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "76 DL 1068 3 T.OWY;> f Hebrew JY>[ \n", "107 NaN 206 51 J:KUL.W. m Hebrew KLH[ \n", "141 DF_DF 141 3 J.AN.IX;HW. m Hebrew NWX[ \n", "143 NaN 468 10 C@M:R@H. unknown Hebrew CMR[ \n", "\n", " nme1 nu1 number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 \\\n", "36 absent sg 205 verb T= absent unknown unknown unknown \n", "76 absent sg 449 verb T= absent unknown unknown unknown \n", "107 absent pl 675 verb J absent unknown unknown unknown \n", "141 absent sg 953 verb J HW m sg p3 \n", "143 NaN unknown 961 verb NaN H f sg p3 \n", "\n", " ps1 rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 \\\n", "36 p3 7211 verb NaN absent NaN H hif wayq \n", "76 p3 7211 verb NaN absent NaN H hif impf \n", "107 p3 781 verb NaN absent W absent pual wayq \n", "141 p3 7211 verb NaN absent NaN H hif wayq \n", "143 unknown 3149 verb a absent NaN absent qal infc \n", "\n", " paragogicNun emphaticImpv Transposition WayCohortEnding \\\n", "36 False False False False \n", "76 False False False False \n", "107 False False False False \n", "141 False False False False \n", "143 False False False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "36 False False \n", "76 False False \n", "107 False False \n", "141 False False \n", "143 False False " ] }, "execution_count": 184, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHSallVerbalMorphologyOTST625_sampled.head()" ] }, { "cell_type": "code", "execution_count": 185, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tense_counts= BHSallVerbalMorphologyOTST625_sampled['bol_vt1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "tense_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "ps_counts= BHSallVerbalMorphologyOTST625_sampled['ps1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "ps_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall PS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "gn_counts= BHSallVerbalMorphologyOTST625_sampled['gn1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "gn_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall GN Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vc_counts= BHSallVerbalMorphologyOTST625_sampled['bol_dict_vc1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vc_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VC Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n", "\n", "vs_counts= BHSallVerbalMorphologyOTST625_sampled['vs1'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "vs_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall VS Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Exporting the Sampled Data" ] }, { "cell_type": "code", "execution_count": 186, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphologyOTST551_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_morphology_verbs_OTST_551_Qualifier-Selection_unfiltered_v0.3.xlsx')" ] }, { "cell_type": "code", "execution_count": 187, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphologyOTST552_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_morphology_verbs_OTST_552_Qualifier-Selection_unfiltered_v0.3.xlsx')" ] }, { "cell_type": "code", "execution_count": 188, "metadata": {}, "outputs": [], "source": [ "BHSallVerbalMorphologyOTST625_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_morphology_verbs_OTST_625_Qualifier-Selection_unfiltered_v0.3.xlsx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reges_I 21:1-17" ] }, { "cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1bol_bhsa_word_order1bol_dict_EN1bol_dict_HebArm1bol_dict_abc1bol_dict_vc1bol_lexeme_occurrences1bol_monad_num1bol_qere_presence1bol_vt1dagesh1freq_lex1freq_occ1g_word_noaccent1gn1language1lex1nme1nu1number1pdp1pfm1prs1prs_gn1prs_nu1prs_ps1ps1rank_occ1sp1st1uvf1vbe1vbs1vs1vt1paragogicNunemphaticImpvTranspositionWayCohortEndingPielPualHit_wo_DF_compLengtheningPielPualHit_w_DoubleDoubling
31620316211_Kings211192988wordיְהִ֗י192988qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey35611929870wayqNaN3561866J:HIJmHebrewHJH[absentsg16911verbJabsentunknownunknownunknownp338verbNaNabsentNaNabsentqalwayqFalseFalseFalseFalseFalseFalse
31621316221_Kings211192995wordהָיָ֛ה192995qal: be, happen, become, occur; ni: be realize...היה1864i-guttural, iii-hey35611929940perfNaN3561761H@J@HmHebrewHJH[absentsg16918verbabsentabsentunknownunknownunknownp345verbNaNabsentNaNabsentqalperfFalseFalseFalseFalseFalseFalse
31622316231_Kings212193009wordיְדַבֵּ֣ר193009qal: speak; ni: speak; pi: speak; pu: be spoke...דבר I1616iii-guttural11381930080wayqNaN1138240J:DAB.;RmHebrewDBR[absentsg16932verbJabsentunknownunknownunknownp3179verbNaNabsentNaNabsentpielwayqFalseFalseFalseFalseFalseFalse
31623316241_Kings212193014wordאמֹר֩׀193014qal: say, think; ni: be said, be called; hi: d...אמר I545i-aleph53071930130infcNaN53071911>MORunknownHebrew>MR[NaNunknown16937verbNaNabsentunknownunknownunknownunknown20verbaabsentNaNabsentqalinfcFalseFalseFalseFalseFalseFalse
31624316251_Kings212193015wordתְּנָה־193015qal: give, place; ni: be given, put; ho: be gi...נתן5268i-nun20101930140impvDL201024T.:N@HmHebrewNTN[absentsg16938verbNaNabsentunknownunknownunknownp21565verbNaNabsentH=absentqalimpvFalseTrueFalseFalseFalseFalse
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 TEXT1 bol_bhsa_word_order1 \\\n", "31620 31621 1_Kings 21 1 192988 word יְהִ֗י 192988 \n", "31621 31622 1_Kings 21 1 192995 word הָיָ֛ה 192995 \n", "31622 31623 1_Kings 21 2 193009 word יְדַבֵּ֣ר 193009 \n", "31623 31624 1_Kings 21 2 193014 word אמֹר֩׀ 193014 \n", "31624 31625 1_Kings 21 2 193015 word תְּנָה־ 193015 \n", "\n", " bol_dict_EN1 bol_dict_HebArm1 \\\n", "31620 qal: be, happen, become, occur; ni: be realize... היה \n", "31621 qal: be, happen, become, occur; ni: be realize... היה \n", "31622 qal: speak; ni: speak; pi: speak; pu: be spoke... דבר I \n", "31623 qal: say, think; ni: be said, be called; hi: d... אמר I \n", "31624 qal: give, place; ni: be given, put; ho: be gi... נתן \n", "\n", " bol_dict_abc1 bol_dict_vc1 bol_lexeme_occurrences1 \\\n", "31620 1864 i-guttural, iii-hey 3561 \n", "31621 1864 i-guttural, iii-hey 3561 \n", "31622 1616 iii-guttural 1138 \n", "31623 545 i-aleph 5307 \n", "31624 5268 i-nun 2010 \n", "\n", " bol_monad_num1 bol_qere_presence1 bol_vt1 dagesh1 freq_lex1 \\\n", "31620 192987 0 wayq NaN 3561 \n", "31621 192994 0 perf NaN 3561 \n", "31622 193008 0 wayq NaN 1138 \n", "31623 193013 0 infc NaN 5307 \n", "31624 193014 0 impv DL 2010 \n", "\n", " freq_occ1 g_word_noaccent1 gn1 language1 lex1 nme1 nu1 \\\n", "31620 866 J:HIJ m Hebrew HJH[ absent sg \n", "31621 761 H@J@H m Hebrew HJH[ absent sg \n", "31622 240 J:DAB.;R m Hebrew DBR[ absent sg \n", "31623 1911 >MOR unknown Hebrew >MR[ NaN unknown \n", "31624 24 T.:N@H m Hebrew NTN[ absent sg \n", "\n", " number1 pdp1 pfm1 prs1 prs_gn1 prs_nu1 prs_ps1 ps1 \\\n", "31620 16911 verb J absent unknown unknown unknown p3 \n", "31621 16918 verb absent absent unknown unknown unknown p3 \n", "31622 16932 verb J absent unknown unknown unknown p3 \n", "31623 16937 verb NaN absent unknown unknown unknown unknown \n", "31624 16938 verb NaN absent unknown unknown unknown p2 \n", "\n", " rank_occ1 sp1 st1 uvf1 vbe1 vbs1 vs1 vt1 paragogicNun \\\n", "31620 38 verb NaN absent NaN absent qal wayq False \n", "31621 45 verb NaN absent NaN absent qal perf False \n", "31622 179 verb NaN absent NaN absent piel wayq False \n", "31623 20 verb a absent NaN absent qal infc False \n", "31624 1565 verb NaN absent H= absent qal impv False \n", "\n", " emphaticImpv Transposition WayCohortEnding \\\n", "31620 False False False \n", "31621 False False False \n", "31622 False False False \n", "31623 False False False \n", "31624 True False False \n", "\n", " PielPualHit_wo_DF_compLengthening PielPualHit_w_DoubleDoubling \n", "31620 False False \n", "31621 False False \n", "31622 False False \n", "31623 False False \n", "31624 False False " ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Reges21Morphology=BHSallVerbalMorphology[\n", " (BHSallVerbalMorphology['S1']=='1_Kings') \n", " & (BHSallVerbalMorphology['S2']==21) \n", " & (BHSallVerbalMorphology['S3']<18) \n", " ]\n", "Reges21Morphology.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges21Morphology.describe()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "Reges21Morphology=Reges21Morphology \\\n", " .groupby(['S3']) \\\n", " .sample(n=1, replace=True)\\\n", " .sort_values(['bol_monad_num1',\n", " 'bol_dict_vc1',\n", " 'vs1',\n", " 'bol_vt1',\n", " 'ps1',\n", " 'nu1',\n", " 'gn1',\n", " 'prs_ps1',\n", " 'prs_nu1',\n", " 'prs_gn1'], \n", " ascending=True)\n", "Reges21Morphology.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges21Morphology.describe()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges21Morphology.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/OTST551-2_exams_og/OTST552_week12_midterm-sample_Reges21_morphology_selection.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Syntax: Phrase Function Analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Catching clauses for OTST551" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Genesis\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 245, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 4.08s 305 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Genesis 1:5יֹ֥ום אֶחָֽד׃ פ יֹ֥ום אֶחָֽד׃ פ יֹ֥ום
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Genesis='''\n", "verse book=Genesis chapter=1|3|6|12|13|18|19|20|21|22|25|26|27\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "'''\n", "Genesis = BHSa4c.search(Genesis)\n", "BHSa4c.table(Genesis, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Exodus\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 246, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 4.25s 34 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Exodus 20:2אָֽנֹכִ֖י֙ יְהוָ֣ה אֱלֹהֶ֑֔יךָ אָֽנֹכִ֖י֙ אָֽנֹכִ֖י֙
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Exodus='''\n", "verse book=Exodus chapter=20\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Exodus = BHSa4c.search(Exodus)\n", "BHSa4c.table(Exodus, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Numeri\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 247, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.21s 0 results\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Numeri='''\n", "verse book=Numeri chapter=6 verse=22|23|24|25|26|27\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Numeri = BHSa4c.search(Numeri)\n", "BHSa4c.table(Numeri, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Josua\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 248, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 5.57s 66 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Joshua 1:2וְעַתָּה֩ וְוְ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Josua='''\n", "verse book=Josua chapter=1|10\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Josua = BHSa4c.search(Josua)\n", "BHSa4c.table(Josua, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Judices\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 249, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 5.08s 22 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Judges 19:1וּמֶ֖לֶךְ אֵ֣ין בְּיִשְׂרָאֵ֑ל וּוּ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Judices='''\n", "verse book=Judices chapter=19\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Judices = BHSa4c.search(Judices)\n", "BHSa4c.table(Judices, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Samuel_I\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 250, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.83s 87 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
11_Samuel 1:2וְלֹו֙ שְׁתֵּ֣י נָשִׁ֔ים וְוְ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Samuel_I='''\n", "verse book=Samuel_I chapter=1|9\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Samuel_I = BHSa4c.search(Samuel_I)\n", "BHSa4c.table(Samuel_I, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Reges_I\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 251, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.68s 17 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
11_Kings 21:2טֹ֣וב מִמֶּ֑נּוּ טֹ֣וב טֹ֣וב
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Reges_I='''\n", "verse book=Reges_I chapter=21\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Reges_I = BHSa4c.search(Reges_I)\n", "BHSa4c.table(Reges_I, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Reges_II\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 252, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.99s 50 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
12_Kings 6:10לֹ֥א אַחַ֖ת לֹ֥א לֹ֥א
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Reges_II='''\n", "verse book=Reges_II chapter=6\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Reges_II = BHSa4c.search(Reges_II)\n", "BHSa4c.table(Reges_II, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Jeremia\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 253, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.22s 59 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Jeremiah 37:10אִ֤ישׁ בְּאָהֳלֹו֙ אִ֤ישׁ אִ֤ישׁ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Jeremia='''\n", "verse book=Jeremia chapter=37|38|39\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Jeremia = BHSa4c.search(Jeremia)\n", "BHSa4c.table(Jeremia, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Jona\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 254, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.41s 19 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Jonah 1:5אִ֣ישׁ אֶל־אֱלֹהָיו֒ אִ֣ישׁ אִ֣ישׁ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Jona='''\n", "verse book=Jona chapter=1\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Jona = BHSa4c.search(Jona)\n", "BHSa4c.table(Jona, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Ruth\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 255, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.19s 25 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Ruth 1:1שְׁפֹ֣ט הַשֹּׁפְטִ֔ים שְׁפֹ֣ט שְׁפֹ֣ט
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Ruth='''\n", "verse book=Ruth chapter=1\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word bol_lexeme_occurrences<200\n", " /-/ \n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb|.*i.*|.*gem.*\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Ruth = BHSa4c.search(Ruth)\n", "BHSa4c.table(Ruth, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST551 export" ] }, { "cell_type": "code", "execution_count": 256, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Ruth, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_phrase-function_OTST_551_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Sampling for OTST551" ] }, { "cell_type": "code", "execution_count": 257, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3det3function3rela3typ3NODE4TYPE4TEXT4bol_lexeme_occurrences4bol_monad_num4bol_qere_presence4bol_sequence_number_clause4bol_sequence_number_clause_atom4bol_sequence_number_phrase4bol_sequence_number_phrase_atom4language4
01Genesis151414358verseוַיִּקְרָ֨א אֱלֹהִ֤ים׀ לָאֹור֙ יֹ֔ום וְלַחֹ֖שׁ...Genesis1427567clauseיֹ֥ום אֶחָֽד׃ פNNCNaNNmCl651590phraseיֹ֥ום אֶחָֽד׃ פundPreCNaNNP77wordיֹ֥ום230477015154949Hebrew
12Genesis151414358verseוַיִּקְרָ֨א אֱלֹהִ֤ים׀ לָאֹור֙ יֹ֔ום וְלַחֹ֖שׁ...Genesis1427567clauseיֹ֥ום אֶחָֽד׃ פNNCNaNNmCl651590phraseיֹ֥ום אֶחָֽד׃ פundPreCNaNNP78wordאֶחָֽד׃ פ97078015164949Hebrew
23Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427592clauseאֲשֶׁ֥ר זַרְעֹו־בֹ֖וQNCAttrNmCl651664phraseאֲשֶׁ֥רNaNRelaNaNCP195wordאֲשֶׁ֥ר550019504042123130Hebrew
34Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427592clauseאֲשֶׁ֥ר זַרְעֹו־בֹ֖וQNCAttrNmCl651665phraseזַרְעֹו־detSubjNaNNP196wordזַרְעֹו־22919604042124131Hebrew
45Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427592clauseאֲשֶׁ֥ר זַרְעֹו־בֹ֖וQNCAttrNmCl651666phraseבֹ֖וdetPreCNaNPP197wordבֹ֖ו1554119704043125132Hebrew
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "0 1 Genesis 1 5 1414358 verse \n", "1 2 Genesis 1 5 1414358 verse \n", "2 3 Genesis 1 11 1414364 verse \n", "3 4 Genesis 1 11 1414364 verse \n", "4 5 Genesis 1 11 1414364 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיִּקְרָ֨א אֱלֹהִ֤ים׀ לָאֹור֙ יֹ֔ום וְלַחֹ֖שׁ... Genesis 1 \n", "1 וַיִּקְרָ֨א אֱלֹהִ֤ים׀ לָאֹור֙ יֹ֔ום וְלַחֹ֖שׁ... Genesis 1 \n", "2 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "3 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "4 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 NODE3 \\\n", "0 427567 clause יֹ֥ום אֶחָֽד׃ פ N NC NaN NmCl 651590 \n", "1 427567 clause יֹ֥ום אֶחָֽד׃ פ N NC NaN NmCl 651590 \n", "2 427592 clause אֲשֶׁ֥ר זַרְעֹו־בֹ֖ו Q NC Attr NmCl 651664 \n", "3 427592 clause אֲשֶׁ֥ר זַרְעֹו־בֹ֖ו Q NC Attr NmCl 651665 \n", "4 427592 clause אֲשֶׁ֥ר זַרְעֹו־בֹ֖ו Q NC Attr NmCl 651666 \n", "\n", " TYPE3 TEXT3 det3 function3 rela3 typ3 NODE4 TYPE4 \\\n", "0 phrase יֹ֥ום אֶחָֽד׃ פ und PreC NaN NP 77 word \n", "1 phrase יֹ֥ום אֶחָֽד׃ פ und PreC NaN NP 78 word \n", "2 phrase אֲשֶׁ֥ר NaN Rela NaN CP 195 word \n", "3 phrase זַרְעֹו־ det Subj NaN NP 196 word \n", "4 phrase בֹ֖ו det PreC NaN PP 197 word \n", "\n", " TEXT4 bol_lexeme_occurrences4 bol_monad_num4 bol_qere_presence4 \\\n", "0 יֹ֥ום 2304 77 0 \n", "1 אֶחָֽד׃ פ 970 78 0 \n", "2 אֲשֶׁ֥ר 5500 195 0 \n", "3 זַרְעֹו־ 229 196 0 \n", "4 בֹ֖ו 15541 197 0 \n", "\n", " bol_sequence_number_clause4 bol_sequence_number_clause_atom4 \\\n", "0 15 15 \n", "1 15 16 \n", "2 40 42 \n", "3 40 42 \n", "4 40 43 \n", "\n", " bol_sequence_number_phrase4 bol_sequence_number_phrase_atom4 language4 \n", "0 49 49 Hebrew \n", "1 49 49 Hebrew \n", "2 123 130 Hebrew \n", "3 124 131 Hebrew \n", "4 125 132 Hebrew " ] }, "execution_count": 257, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST551_phrase_selection=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_phrase-function_OTST_551_Qualifier-Selection_unfiltered_v0.3.tsv', delimiter='\\t', encoding='utf-16')\n", "BHS_OTST551_phrase_selection.head()" ] }, { "cell_type": "code", "execution_count": 258, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 684 entries, 0 to 683\n", "Data columns (total 34 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 684 non-null int64 \n", " 1 S1 684 non-null object\n", " 2 S2 684 non-null int64 \n", " 3 S3 684 non-null int64 \n", " 4 NODE1 684 non-null int64 \n", " 5 TYPE1 684 non-null object\n", " 6 TEXT1 684 non-null object\n", " 7 book1 684 non-null object\n", " 8 chapter1 684 non-null int64 \n", " 9 NODE2 684 non-null int64 \n", " 10 TYPE2 684 non-null object\n", " 11 TEXT2 684 non-null object\n", " 12 domain2 684 non-null object\n", " 13 kind2 684 non-null object\n", " 14 rela2 250 non-null object\n", " 15 typ2 684 non-null object\n", " 16 NODE3 684 non-null int64 \n", " 17 TYPE3 684 non-null object\n", " 18 TEXT3 684 non-null object\n", " 19 det3 462 non-null object\n", " 20 function3 684 non-null object\n", " 21 rela3 1 non-null object\n", " 22 typ3 684 non-null object\n", " 23 NODE4 684 non-null int64 \n", " 24 TYPE4 684 non-null object\n", " 25 TEXT4 673 non-null object\n", " 26 bol_lexeme_occurrences4 684 non-null int64 \n", " 27 bol_monad_num4 684 non-null int64 \n", " 28 bol_qere_presence4 684 non-null int64 \n", " 29 bol_sequence_number_clause4 684 non-null int64 \n", " 30 bol_sequence_number_clause_atom4 684 non-null int64 \n", " 31 bol_sequence_number_phrase4 684 non-null int64 \n", " 32 bol_sequence_number_phrase_atom4 684 non-null int64 \n", " 33 language4 684 non-null object\n", "dtypes: int64(15), object(19)\n", "memory usage: 181.8+ KB\n" ] } ], "source": [ "BHS_OTST551_phrase_selection.info()" ] }, { "cell_type": "code", "execution_count": 259, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['PreC', 'Rela', 'Subj', 'Conj', 'Intj', 'Modi', 'Frnt', 'Time', 'Loca', 'Ques', 'Nega', 'Cmpl', 'Voct', 'Pred', 'NCop', 'PreS', 'Objc', 'IntS', 'ModS', 'Adju']\n" ] } ], "source": [ "vt=BHS_OTST551_phrase_selection.function3.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 260, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 178 entries, 3 to 681\n", "Data columns (total 34 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 178 non-null int64 \n", " 1 S1 178 non-null object\n", " 2 S2 178 non-null int64 \n", " 3 S3 178 non-null int64 \n", " 4 NODE1 178 non-null int64 \n", " 5 TYPE1 178 non-null object\n", " 6 TEXT1 178 non-null object\n", " 7 book1 178 non-null object\n", " 8 chapter1 178 non-null int64 \n", " 9 NODE2 178 non-null int64 \n", " 10 TYPE2 178 non-null object\n", " 11 TEXT2 178 non-null object\n", " 12 domain2 178 non-null object\n", " 13 kind2 178 non-null object\n", " 14 rela2 45 non-null object\n", " 15 typ2 178 non-null object\n", " 16 NODE3 178 non-null int64 \n", " 17 TYPE3 178 non-null object\n", " 18 TEXT3 178 non-null object\n", " 19 det3 148 non-null object\n", " 20 function3 178 non-null object\n", " 21 rela3 1 non-null object\n", " 22 typ3 178 non-null object\n", " 23 NODE4 178 non-null int64 \n", " 24 TYPE4 178 non-null object\n", " 25 TEXT4 178 non-null object\n", " 26 bol_lexeme_occurrences4 178 non-null int64 \n", " 27 bol_monad_num4 178 non-null int64 \n", " 28 bol_qere_presence4 178 non-null int64 \n", " 29 bol_sequence_number_clause4 178 non-null int64 \n", " 30 bol_sequence_number_clause_atom4 178 non-null int64 \n", " 31 bol_sequence_number_phrase4 178 non-null int64 \n", " 32 bol_sequence_number_phrase_atom4 178 non-null int64 \n", " 33 language4 178 non-null object\n", "dtypes: int64(15), object(19)\n", "memory usage: 48.7+ KB\n" ] } ], "source": [ "BHS_OTST551_phrase_selection=BHS_OTST551_phrase_selection[\n", " (\n", " (BHS_OTST551_phrase_selection['function3']=='Pred')\n", " | (BHS_OTST551_phrase_selection['function3']=='Subj')\n", " | (BHS_OTST551_phrase_selection['function3']=='Objc')\n", " | (BHS_OTST551_phrase_selection['function3']=='PreO')\n", " | (BHS_OTST551_phrase_selection['function3']=='Nega')\n", " | (BHS_OTST551_phrase_selection['function3']=='PreS')\n", " )\n", " ]\n", "BHS_OTST551_phrase_selection.info()" ] }, { "cell_type": "code", "execution_count": 263, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['Subj', 'Nega', 'Pred', 'PreS', 'Objc']\n" ] } ], "source": [ "vt=BHS_OTST551_phrase_selection.function3.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 264, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3det3function3rela3typ3NODE4TYPE4TEXT4bol_lexeme_occurrences4bol_monad_num4bol_qere_presence4bol_sequence_number_clause4bol_sequence_number_clause_atom4bol_sequence_number_phrase4bol_sequence_number_phrase_atom4language4
284285Genesis27211415102verseוַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥...Genesis27430309clauseאִם־לֹֽא׃QWPNaNEllp659915phraseלֹֽא׃NaNNegaNaNNegP13990wordלֹֽא׃51671399002760285783788771Hebrew
5405412_Kings6121423958verseוַיֹּ֨אמֶר֙ אַחַ֣ד מֵֽעֲבָדָ֔יו לֹ֖וא אֲדֹנִ֣י...Reges_II6465612clauseלֹ֖ואQNCNaNNmCl766521phraseלֹ֖ואNaNNegaNaNNegP198377wordלֹ֖וא516719837603800239137114947121774Hebrew
5345352_Kings6101423956verseוַיִּשְׁלַ֞ח מֶ֣לֶךְ יִשְׂרָאֵ֗ל אֶֽל־הַמָּקֹ֞...Reges_II6465604clauseוְלֹ֥א שְׁתָּֽיִם׃NNCNaNNmCl766498phraseלֹ֥אNaNNegaNaNNegP198342wordלֹ֥א516719834103799439127114924121750Hebrew
110111Genesis18151414793verseוַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי...Genesis18429015clauseלֹ֖אQNCNaNNmCl656074phraseלֹ֖אNaNNegaNaNNegP8072wordלֹ֖א5167807201466154045374775Hebrew
4614621_Samuel941421665verseוַיַּעֲבֹ֧ר בְּהַר־אֶפְרַ֛יִם וַיַּעֲבֹ֥ר בְּא...Samuel_I9454791clauseוָאַ֔יִןNNCNaNNmCl734182phraseאַ֔יִןNaNNegaNaNNegP145581wordאַ֔יִן788145580027189280898261187542Hebrew
139140Genesis19181414829verseוַיֹּ֥אמֶר לֹ֖וט אֲלֵהֶ֑ם אַל־נָ֖א אֲדֹנָֽי׃Genesis19429197clauseאַל־נָ֖אQNCNaNNmCl656595phraseאַל־NaNNegaNaNNegP8834wordאַל־726883401648172550585306Hebrew
124125Genesis1921414813verseוַיֹּ֜אמֶר הִנֶּ֣ה נָּא־אֲדֹנַ֗י ס֣וּרוּ נָ֠א ...Genesis19429118clauseלֹּ֔אQNCNaNNmCl656365phraseלֹּ֔אNaNNegaNaNNegP8473wordלֹּ֔א5167847301569164448285067Hebrew
4984991_Samuel9201421681verseוְלָאֲתֹנֹ֞ות הָאֹבְדֹ֣ות לְךָ֗ הַיֹּום֙ שְׁלֹ...Samuel_I9454895clauseהֲלֹ֣וא לְךָ֔ וּלְכֹ֖ל בֵּ֥ית אָבִֽיךָ׃ סQNCNaNNmCl734476phraseלֹ֣ואNaNNegaNaNNegP146007wordלֹ֣וא5167146006027293281948290587840Hebrew
110111Genesis18151414793verseוַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי...Genesis18429015clauseלֹ֖אQNCNaNNmCl656074phraseלֹ֖אNaNNegaNaNNegP8072wordלֹ֖א5167807201466154045374775Hebrew
284285Genesis27211415102verseוַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥...Genesis27430309clauseאִם־לֹֽא׃QWPNaNEllp659915phraseלֹֽא׃NaNNegaNaNNegP13990wordלֹֽא׃51671399002760285783788771Hebrew
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "284 285 Genesis 27 21 1415102 verse \n", "540 541 2_Kings 6 12 1423958 verse \n", "534 535 2_Kings 6 10 1423956 verse \n", "110 111 Genesis 18 15 1414793 verse \n", "461 462 1_Samuel 9 4 1421665 verse \n", "139 140 Genesis 19 18 1414829 verse \n", "124 125 Genesis 19 2 1414813 verse \n", "498 499 1_Samuel 9 20 1421681 verse \n", "110 111 Genesis 18 15 1414793 verse \n", "284 285 Genesis 27 21 1415102 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "284 וַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥... Genesis 27 \n", "540 וַיֹּ֨אמֶר֙ אַחַ֣ד מֵֽעֲבָדָ֔יו לֹ֖וא אֲדֹנִ֣י... Reges_II 6 \n", "534 וַיִּשְׁלַ֞ח מֶ֣לֶךְ יִשְׂרָאֵ֗ל אֶֽל־הַמָּקֹ֞... Reges_II 6 \n", "110 וַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי... Genesis 18 \n", "461 וַיַּעֲבֹ֧ר בְּהַר־אֶפְרַ֛יִם וַיַּעֲבֹ֥ר בְּא... Samuel_I 9 \n", "139 וַיֹּ֥אמֶר לֹ֖וט אֲלֵהֶ֑ם אַל־נָ֖א אֲדֹנָֽי׃ Genesis 19 \n", "124 וַיֹּ֜אמֶר הִנֶּ֣ה נָּא־אֲדֹנַ֗י ס֣וּרוּ נָ֠א ... Genesis 19 \n", "498 וְלָאֲתֹנֹ֞ות הָאֹבְדֹ֣ות לְךָ֗ הַיֹּום֙ שְׁלֹ... Samuel_I 9 \n", "110 וַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי... Genesis 18 \n", "284 וַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥... Genesis 27 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 \\\n", "284 430309 clause אִם־לֹֽא׃ Q WP \n", "540 465612 clause לֹ֖וא Q NC \n", "534 465604 clause וְלֹ֥א שְׁתָּֽיִם׃ N NC \n", "110 429015 clause לֹ֖א Q NC \n", "461 454791 clause וָאַ֔יִן N NC \n", "139 429197 clause אַל־נָ֖א Q NC \n", "124 429118 clause לֹּ֔א Q NC \n", "498 454895 clause הֲלֹ֣וא לְךָ֔ וּלְכֹ֖ל בֵּ֥ית אָבִֽיךָ׃ ס Q NC \n", "110 429015 clause לֹ֖א Q NC \n", "284 430309 clause אִם־לֹֽא׃ Q WP \n", "\n", " rela2 typ2 NODE3 TYPE3 TEXT3 det3 function3 rela3 typ3 NODE4 \\\n", "284 NaN Ellp 659915 phrase לֹֽא׃ NaN Nega NaN NegP 13990 \n", "540 NaN NmCl 766521 phrase לֹ֖וא NaN Nega NaN NegP 198377 \n", "534 NaN NmCl 766498 phrase לֹ֥א NaN Nega NaN NegP 198342 \n", "110 NaN NmCl 656074 phrase לֹ֖א NaN Nega NaN NegP 8072 \n", "461 NaN NmCl 734182 phrase אַ֔יִן NaN Nega NaN NegP 145581 \n", "139 NaN NmCl 656595 phrase אַל־ NaN Nega NaN NegP 8834 \n", "124 NaN NmCl 656365 phrase לֹּ֔א NaN Nega NaN NegP 8473 \n", "498 NaN NmCl 734476 phrase לֹ֣וא NaN Nega NaN NegP 146007 \n", "110 NaN NmCl 656074 phrase לֹ֖א NaN Nega NaN NegP 8072 \n", "284 NaN Ellp 659915 phrase לֹֽא׃ NaN Nega NaN NegP 13990 \n", "\n", " TYPE4 TEXT4 bol_lexeme_occurrences4 bol_monad_num4 \\\n", "284 word לֹֽא׃ 5167 13990 \n", "540 word לֹ֖וא 5167 198376 \n", "534 word לֹ֥א 5167 198341 \n", "110 word לֹ֖א 5167 8072 \n", "461 word אַ֔יִן 788 145580 \n", "139 word אַל־ 726 8834 \n", "124 word לֹּ֔א 5167 8473 \n", "498 word לֹ֣וא 5167 146006 \n", "110 word לֹ֖א 5167 8072 \n", "284 word לֹֽא׃ 5167 13990 \n", "\n", " bol_qere_presence4 bol_sequence_number_clause4 \\\n", "284 0 2760 \n", "540 0 38002 \n", "534 0 37994 \n", "110 0 1466 \n", "461 0 27189 \n", "139 0 1648 \n", "124 0 1569 \n", "498 0 27293 \n", "110 0 1466 \n", "284 0 2760 \n", "\n", " bol_sequence_number_clause_atom4 bol_sequence_number_phrase4 \\\n", "284 2857 8378 \n", "540 39137 114947 \n", "534 39127 114924 \n", "110 1540 4537 \n", "461 28089 82611 \n", "139 1725 5058 \n", "124 1644 4828 \n", "498 28194 82905 \n", "110 1540 4537 \n", "284 2857 8378 \n", "\n", " bol_sequence_number_phrase_atom4 language4 \n", "284 8771 Hebrew \n", "540 121774 Hebrew \n", "534 121750 Hebrew \n", "110 4775 Hebrew \n", "461 87542 Hebrew \n", "139 5306 Hebrew \n", "124 5067 Hebrew \n", "498 87840 Hebrew \n", "110 4775 Hebrew \n", "284 8771 Hebrew " ] }, "execution_count": 264, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHS_OTST551_phrase_selection_sampled=BHS_OTST551_phrase_selection \\\n", " .groupby(['function3'\n", " ]) \\\n", " .sample(n=100, random_state=1, replace=True)\\\n", " .sort_values(['function3'\n", " ], \n", " ascending=True)\n", "BHS_OTST551_phrase_selection_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": 265, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 500 entries, 284 to 492\n", "Data columns (total 34 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 500 non-null int64 \n", " 1 S1 500 non-null object\n", " 2 S2 500 non-null int64 \n", " 3 S3 500 non-null int64 \n", " 4 NODE1 500 non-null int64 \n", " 5 TYPE1 500 non-null object\n", " 6 TEXT1 500 non-null object\n", " 7 book1 500 non-null object\n", " 8 chapter1 500 non-null int64 \n", " 9 NODE2 500 non-null int64 \n", " 10 TYPE2 500 non-null object\n", " 11 TEXT2 500 non-null object\n", " 12 domain2 500 non-null object\n", " 13 kind2 500 non-null object\n", " 14 rela2 187 non-null object\n", " 15 typ2 500 non-null object\n", " 16 NODE3 500 non-null int64 \n", " 17 TYPE3 500 non-null object\n", " 18 TEXT3 500 non-null object\n", " 19 det3 200 non-null object\n", " 20 function3 500 non-null object\n", " 21 rela3 2 non-null object\n", " 22 typ3 500 non-null object\n", " 23 NODE4 500 non-null int64 \n", " 24 TYPE4 500 non-null object\n", " 25 TEXT4 500 non-null object\n", " 26 bol_lexeme_occurrences4 500 non-null int64 \n", " 27 bol_monad_num4 500 non-null int64 \n", " 28 bol_qere_presence4 500 non-null int64 \n", " 29 bol_sequence_number_clause4 500 non-null int64 \n", " 30 bol_sequence_number_clause_atom4 500 non-null int64 \n", " 31 bol_sequence_number_phrase4 500 non-null int64 \n", " 32 bol_sequence_number_phrase_atom4 500 non-null int64 \n", " 33 language4 500 non-null object\n", "dtypes: int64(15), object(19)\n", "memory usage: 136.7+ KB\n" ] } ], "source": [ "BHS_OTST551_phrase_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": 266, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3det3function3rela3typ3NODE4TYPE4TEXT4bol_lexeme_occurrences4bol_monad_num4bol_qere_presence4bol_sequence_number_clause4bol_sequence_number_clause_atom4bol_sequence_number_phrase4bol_sequence_number_phrase_atom4language4
284285Genesis27211415102verseוַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥...Genesis27430309clauseאִם־לֹֽא׃QWPNaNEllp659915phraseלֹֽא׃NaNNegaNaNNegP13990wordלֹֽא׃51671399002760285783788771Hebrew
5405412_Kings6121423958verseוַיֹּ֨אמֶר֙ אַחַ֣ד מֵֽעֲבָדָ֔יו לֹ֖וא אֲדֹנִ֣י...Reges_II6465612clauseלֹ֖ואQNCNaNNmCl766521phraseלֹ֖ואNaNNegaNaNNegP198377wordלֹ֖וא516719837603800239137114947121774Hebrew
5345352_Kings6101423956verseוַיִּשְׁלַ֞ח מֶ֣לֶךְ יִשְׂרָאֵ֗ל אֶֽל־הַמָּקֹ֞...Reges_II6465604clauseוְלֹ֥א שְׁתָּֽיִם׃NNCNaNNmCl766498phraseלֹ֥אNaNNegaNaNNegP198342wordלֹ֥א516719834103799439127114924121750Hebrew
110111Genesis18151414793verseוַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי...Genesis18429015clauseלֹ֖אQNCNaNNmCl656074phraseלֹ֖אNaNNegaNaNNegP8072wordלֹ֖א5167807201466154045374775Hebrew
4614621_Samuel941421665verseוַיַּעֲבֹ֧ר בְּהַר־אֶפְרַ֛יִם וַיַּעֲבֹ֥ר בְּא...Samuel_I9454791clauseוָאַ֔יִןNNCNaNNmCl734182phraseאַ֔יִןNaNNegaNaNNegP145581wordאַ֔יִן788145580027189280898261187542Hebrew
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "284 285 Genesis 27 21 1415102 verse \n", "540 541 2_Kings 6 12 1423958 verse \n", "534 535 2_Kings 6 10 1423956 verse \n", "110 111 Genesis 18 15 1414793 verse \n", "461 462 1_Samuel 9 4 1421665 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "284 וַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥... Genesis 27 \n", "540 וַיֹּ֨אמֶר֙ אַחַ֣ד מֵֽעֲבָדָ֔יו לֹ֖וא אֲדֹנִ֣י... Reges_II 6 \n", "534 וַיִּשְׁלַ֞ח מֶ֣לֶךְ יִשְׂרָאֵ֗ל אֶֽל־הַמָּקֹ֞... Reges_II 6 \n", "110 וַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי... Genesis 18 \n", "461 וַיַּעֲבֹ֧ר בְּהַר־אֶפְרַ֛יִם וַיַּעֲבֹ֥ר בְּא... Samuel_I 9 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 NODE3 \\\n", "284 430309 clause אִם־לֹֽא׃ Q WP NaN Ellp 659915 \n", "540 465612 clause לֹ֖וא Q NC NaN NmCl 766521 \n", "534 465604 clause וְלֹ֥א שְׁתָּֽיִם׃ N NC NaN NmCl 766498 \n", "110 429015 clause לֹ֖א Q NC NaN NmCl 656074 \n", "461 454791 clause וָאַ֔יִן N NC NaN NmCl 734182 \n", "\n", " TYPE3 TEXT3 det3 function3 rela3 typ3 NODE4 TYPE4 TEXT4 \\\n", "284 phrase לֹֽא׃ NaN Nega NaN NegP 13990 word לֹֽא׃ \n", "540 phrase לֹ֖וא NaN Nega NaN NegP 198377 word לֹ֖וא \n", "534 phrase לֹ֥א NaN Nega NaN NegP 198342 word לֹ֥א \n", "110 phrase לֹ֖א NaN Nega NaN NegP 8072 word לֹ֖א \n", "461 phrase אַ֔יִן NaN Nega NaN NegP 145581 word אַ֔יִן \n", "\n", " bol_lexeme_occurrences4 bol_monad_num4 bol_qere_presence4 \\\n", "284 5167 13990 0 \n", "540 5167 198376 0 \n", "534 5167 198341 0 \n", "110 5167 8072 0 \n", "461 788 145580 0 \n", "\n", " bol_sequence_number_clause4 bol_sequence_number_clause_atom4 \\\n", "284 2760 2857 \n", "540 38002 39137 \n", "534 37994 39127 \n", "110 1466 1540 \n", "461 27189 28089 \n", "\n", " bol_sequence_number_phrase4 bol_sequence_number_phrase_atom4 language4 \n", "284 8378 8771 Hebrew \n", "540 114947 121774 Hebrew \n", "534 114924 121750 Hebrew \n", "110 4537 4775 Hebrew \n", "461 82611 87542 Hebrew " ] }, "execution_count": 266, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST551_phrase_selection_sampled.drop_duplicates(subset=\"bol_sequence_number_phrase4\", keep='first', inplace=True)\n", "BHS_OTST551_phrase_selection_sampled.head(5)" ] }, { "cell_type": "code", "execution_count": 267, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 92 entries, 284 to 628\n", "Data columns (total 34 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 R 92 non-null int64 \n", " 1 S1 92 non-null object\n", " 2 S2 92 non-null int64 \n", " 3 S3 92 non-null int64 \n", " 4 NODE1 92 non-null int64 \n", " 5 TYPE1 92 non-null object\n", " 6 TEXT1 92 non-null object\n", " 7 book1 92 non-null object\n", " 8 chapter1 92 non-null int64 \n", " 9 NODE2 92 non-null int64 \n", " 10 TYPE2 92 non-null object\n", " 11 TEXT2 92 non-null object\n", " 12 domain2 92 non-null object\n", " 13 kind2 92 non-null object\n", " 14 rela2 24 non-null object\n", " 15 typ2 92 non-null object\n", " 16 NODE3 92 non-null int64 \n", " 17 TYPE3 92 non-null object\n", " 18 TEXT3 92 non-null object\n", " 19 det3 64 non-null object\n", " 20 function3 92 non-null object\n", " 21 rela3 1 non-null object\n", " 22 typ3 92 non-null object\n", " 23 NODE4 92 non-null int64 \n", " 24 TYPE4 92 non-null object\n", " 25 TEXT4 92 non-null object\n", " 26 bol_lexeme_occurrences4 92 non-null int64 \n", " 27 bol_monad_num4 92 non-null int64 \n", " 28 bol_qere_presence4 92 non-null int64 \n", " 29 bol_sequence_number_clause4 92 non-null int64 \n", " 30 bol_sequence_number_clause_atom4 92 non-null int64 \n", " 31 bol_sequence_number_phrase4 92 non-null int64 \n", " 32 bol_sequence_number_phrase_atom4 92 non-null int64 \n", " 33 language4 92 non-null object\n", "dtypes: int64(15), object(19)\n", "memory usage: 25.2+ KB\n" ] } ], "source": [ "BHS_OTST551_phrase_selection_sampled.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST551 raw sampled data" ] }, { "cell_type": "code", "execution_count": 268, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3det3function3rela3typ3NODE4TYPE4TEXT4bol_lexeme_occurrences4bol_monad_num4bol_qere_presence4bol_sequence_number_clause4bol_sequence_number_clause_atom4bol_sequence_number_phrase4bol_sequence_number_phrase_atom4language4
284285Genesis27211415102verseוַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥...Genesis27430309clauseאִם־לֹֽא׃QWPNaNEllp659915phraseלֹֽא׃NaNNegaNaNNegP13990wordלֹֽא׃51671399002760285783788771Hebrew
5405412_Kings6121423958verseוַיֹּ֨אמֶר֙ אַחַ֣ד מֵֽעֲבָדָ֔יו לֹ֖וא אֲדֹנִ֣י...Reges_II6465612clauseלֹ֖ואQNCNaNNmCl766521phraseלֹ֖ואNaNNegaNaNNegP198377wordלֹ֖וא516719837603800239137114947121774Hebrew
5345352_Kings6101423956verseוַיִּשְׁלַ֞ח מֶ֣לֶךְ יִשְׂרָאֵ֗ל אֶֽל־הַמָּקֹ֞...Reges_II6465604clauseוְלֹ֥א שְׁתָּֽיִם׃NNCNaNNmCl766498phraseלֹ֥אNaNNegaNaNNegP198342wordלֹ֥א516719834103799439127114924121750Hebrew
110111Genesis18151414793verseוַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי...Genesis18429015clauseלֹ֖אQNCNaNNmCl656074phraseלֹ֖אNaNNegaNaNNegP8072wordלֹ֖א5167807201466154045374775Hebrew
4614621_Samuel941421665verseוַיַּעֲבֹ֧ר בְּהַר־אֶפְרַ֛יִם וַיַּעֲבֹ֥ר בְּא...Samuel_I9454791clauseוָאַ֔יִןNNCNaNNmCl734182phraseאַ֔יִןNaNNegaNaNNegP145581wordאַ֔יִן788145580027189280898261187542Hebrew
\n", "
" ], "text/plain": [ " R S1 S2 S3 NODE1 TYPE1 \\\n", "284 285 Genesis 27 21 1415102 verse \n", "540 541 2_Kings 6 12 1423958 verse \n", "534 535 2_Kings 6 10 1423956 verse \n", "110 111 Genesis 18 15 1414793 verse \n", "461 462 1_Samuel 9 4 1421665 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "284 וַיֹּ֤אמֶר יִצְחָק֙ אֶֽל־יַעֲקֹ֔ב גְּשָׁה־נָּ֥... Genesis 27 \n", "540 וַיֹּ֨אמֶר֙ אַחַ֣ד מֵֽעֲבָדָ֔יו לֹ֖וא אֲדֹנִ֣י... Reges_II 6 \n", "534 וַיִּשְׁלַ֞ח מֶ֣לֶךְ יִשְׂרָאֵ֗ל אֶֽל־הַמָּקֹ֞... Reges_II 6 \n", "110 וַתְּכַחֵ֨שׁ שָׂרָ֧ה׀ לֵאמֹ֛ר לֹ֥א צָחַ֖קְתִּי... Genesis 18 \n", "461 וַיַּעֲבֹ֧ר בְּהַר־אֶפְרַ֛יִם וַיַּעֲבֹ֥ר בְּא... Samuel_I 9 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 NODE3 \\\n", "284 430309 clause אִם־לֹֽא׃ Q WP NaN Ellp 659915 \n", "540 465612 clause לֹ֖וא Q NC NaN NmCl 766521 \n", "534 465604 clause וְלֹ֥א שְׁתָּֽיִם׃ N NC NaN NmCl 766498 \n", "110 429015 clause לֹ֖א Q NC NaN NmCl 656074 \n", "461 454791 clause וָאַ֔יִן N NC NaN NmCl 734182 \n", "\n", " TYPE3 TEXT3 det3 function3 rela3 typ3 NODE4 TYPE4 TEXT4 \\\n", "284 phrase לֹֽא׃ NaN Nega NaN NegP 13990 word לֹֽא׃ \n", "540 phrase לֹ֖וא NaN Nega NaN NegP 198377 word לֹ֖וא \n", "534 phrase לֹ֥א NaN Nega NaN NegP 198342 word לֹ֥א \n", "110 phrase לֹ֖א NaN Nega NaN NegP 8072 word לֹ֖א \n", "461 phrase אַ֔יִן NaN Nega NaN NegP 145581 word אַ֔יִן \n", "\n", " bol_lexeme_occurrences4 bol_monad_num4 bol_qere_presence4 \\\n", "284 5167 13990 0 \n", "540 5167 198376 0 \n", "534 5167 198341 0 \n", "110 5167 8072 0 \n", "461 788 145580 0 \n", "\n", " bol_sequence_number_clause4 bol_sequence_number_clause_atom4 \\\n", "284 2760 2857 \n", "540 38002 39137 \n", "534 37994 39127 \n", "110 1466 1540 \n", "461 27189 28089 \n", "\n", " bol_sequence_number_phrase4 bol_sequence_number_phrase_atom4 language4 \n", "284 8378 8771 Hebrew \n", "540 114947 121774 Hebrew \n", "534 114924 121750 Hebrew \n", "110 4537 4775 Hebrew \n", "461 82611 87542 Hebrew " ] }, "execution_count": 268, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST551_phrase_selection_sampled.head()" ] }, { "cell_type": "code", "execution_count": 269, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "phrasefunctions= BHS_OTST551_phrase_selection_sampled['function3'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "phrasefunctions.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 271, "metadata": {}, "outputs": [], "source": [ "BHS_OTST551_phrase_selection_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_phrase-function_OTST_551_Qualifier-Selection_filtered_sampled_v0.3.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Catching clauses for OTST552 and OTST625" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Genesis\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.15s 7307 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Genesis 1:1בְּרֵאשִׁ֖ית בָּרָ֣א אֱלֹהִ֑ים אֵ֥ת הַשָּׁמַ֖יִם וְאֵ֥ת הָאָֽרֶץ׃ בְּרֵאשִׁ֖ית בְּ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Genesis='''\n", "verse book=Genesis chapter=1|3|6|12|13|18|19|20|21|22|25|26|27\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "'''\n", "Genesis = BHSa4c.search(Genesis)\n", "BHSa4c.table(Genesis, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Exodus\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.13s 420 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Exodus 20:1וַיְדַבֵּ֣ר אֱלֹהִ֔ים אֵ֛ת כָּל־הַדְּבָרִ֥ים הָאֵ֖לֶּה וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Exodus='''\n", "verse book=Exodus chapter=20\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Exodus = BHSa4c.search(Exodus)\n", "BHSa4c.table(Exodus, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Numeri\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.04s 50 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Numbers 6:22וַיְדַבֵּ֥ר יְהוָ֖ה אֶל־מֹשֶׁ֥ה וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Numeri='''\n", "verse book=Numeri chapter=6 verse=22|23|24|25|26|27\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Numeri = BHSa4c.search(Numeri)\n", "BHSa4c.table(Numeri, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Josua\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.97s 1509 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Joshua 1:1וַיְהִ֗י אַחֲרֵ֛י מֹ֥ות מֹשֶׁ֖ה עֶ֣בֶד יְהוָ֑ה וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Josua='''\n", "verse book=Josua chapter=1|10\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Josua = BHSa4c.search(Josua)\n", "BHSa4c.table(Josua, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Judices\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.20s 792 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Judges 19:1וַיְהִי֙ בַּיָּמִ֣ים הָהֵ֔ם וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Judices='''\n", "verse book=Judices chapter=19\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Judices = BHSa4c.search(Judices)\n", "BHSa4c.table(Judices, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Samuel_I\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 142, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.25s 1290 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
11_Samuel 1:1וַיְהִי֩ אִ֨ישׁ אֶחָ֜ד מִן־הָרָמָתַ֛יִם צֹופִ֖ים מֵהַ֣ר אֶפְרָ֑יִם וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Samuel_I='''\n", "verse book=Samuel_I chapter=1|9\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Samuel_I = BHSa4c.search(Samuel_I)\n", "BHSa4c.table(Samuel_I, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Reges_I\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 143, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.13s 645 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
11_Kings 21:1וַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Reges_I='''\n", "verse book=Reges_I chapter=21\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Reges_I = BHSa4c.search(Reges_I)\n", "BHSa4c.table(Reges_I, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Reges_II\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 144, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.01s 748 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
12_Kings 6:1וַיֹּאמְר֥וּ בְנֵֽי־הַנְּבִיאִ֖ים אֶל־אֱלִישָׁ֑ע וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Reges_II='''\n", "verse book=Reges_II chapter=6\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Reges_II = BHSa4c.search(Reges_II)\n", "BHSa4c.table(Reges_II, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Jeremia\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.38s 1639 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Jeremiah 37:1וַיִּ֨מְלָךְ־מֶ֔לֶךְ צִדְקִיָּ֖הוּ בֶּן־יֹֽאשִׁיָּ֑הוּ תַּ֗חַת כָּנְיָ֨הוּ֙ בֶּן־יְהֹ֣ויָקִ֔ים וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Jeremia='''\n", "verse book=Jeremia chapter=37|38|39\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Jeremia = BHSa4c.search(Jeremia)\n", "BHSa4c.table(Jeremia, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Jona\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.08s 372 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Jonah 1:1וַֽיְהִי֙ דְּבַר־יְהוָ֔ה אֶל־יֹונָ֥ה בֶן־אֲמִתַּ֖י וַֽוַֽ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Jona='''\n", "verse book=Jona chapter=1\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Jona = BHSa4c.search(Jona)\n", "BHSa4c.table(Jona, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Psalmi\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.86s 173 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Psalms 1:1אַ֥שְֽׁרֵי־הָאִ֗ישׁ אַ֥שְֽׁרֵי־הָאִ֗ישׁ אַ֥שְֽׁרֵי־
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Psalmi='''\n", "verse book=Psalmi chapter=1|3\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Psalmi = BHSa4c.search(Psalmi)\n", "BHSa4c.table(Psalmi, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Ruth\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.83s 1285 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Ruth 1:1וַיְהִ֗י בִּימֵי֙ וַוַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Ruth='''\n", "verse book=Ruth chapter=1|2|3\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Ruth = BHSa4c.search(Ruth)\n", "BHSa4c.table(Ruth, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Phrases from Isiah\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 3.14s 140 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclausephraseword
1Isaiah 5:1אָשִׁ֤ירָה נָּא֙ לִֽידִידִ֔י שִׁירַ֥ת דֹּודִ֖י לְכַרְמֹ֑ו אָשִׁ֤ירָה אָשִׁ֤ירָה
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Isiah='''\n", "verse book=Jesaia chapter=5 verse=1|2|3|4|5|6|7\n", " clause typ* kind=NC|VC|WP rela* domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function* typ* rela* det*\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_qere_presence* language* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Isiah = BHSa4c.search(Isiah)\n", "BHSa4c.table(Isiah, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### EXPORT" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST551 export" ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Ruth, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_phrase-function_OTST_551_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST552 export" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Psalmi+Ruth, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_phrase-function_OTST_552_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST625 export" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Psalmi+Ruth+Isiah, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_phrase-function_OTST_625_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Export Reges_I 21:1-17" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "Reges_I_Phrases=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/OTST551-2_exams_og/OTST552_week12_midterm-sample_Reges21_phrases.xlsx')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "Reges_I_Phrases.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reges_I 21:1-17" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection=Reges_I_Phrases[\n", " (Reges_I_Phrases['function3']=='Pred')\n", " | (Reges_I_Phrases['function3']=='Subj')\n", " | (Reges_I_Phrases['function3']=='Objc')\n", " | (Reges_I_Phrases['function3']=='PreC')\n", " | (Reges_I_Phrases['function3']=='Cmpl')\n", " | (Reges_I_Phrases['function3']=='PreO')\n", " | (Reges_I_Phrases['function3']=='Nega')\n", " | (Reges_I_Phrases['function3']=='PreS')\n", " | (Reges_I_Phrases['function3']=='Voct')\n", " ]\n", "Reges_I_phrase_selection.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection = Reges_I_Phrases[(Reges_I_Phrases['S3']<18)]\n", "Reges_I_phrase_selection.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "S3=Reges_I_phrase_selection.S3.unique().tolist()\n", "print(S3)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection.describe()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "Reges_I_phrase_selection=Reges_I_phrase_selection \\\n", " .groupby(['S3','function3']) \\\n", " .sample(n=4, replace=True)\\\n", " .sort_values(['bol_sequence_number_phrase4',\n", " ], \n", " ascending=True)\n", "Reges_I_phrase_selection.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection.describe()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection.drop_duplicates(subset=\"bol_sequence_number_phrase4\", keep='first', inplace=True)\n", "Reges_I_phrase_selection.head(20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection.describe()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Reges_I_phrase_selection.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/OTST551-2_exams_og/OTST552_week12_midterm-sample_Reges21_phrase_selection.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling for OTST552" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_phrase-function_OTST_552_Qualifier-Selection_unfiltered_v0.3.tsv', delimiter='\\t', encoding='utf-16')\n", "BHS_OTST552_phrase_selection.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "vt=BHS_OTST552_phrase_selection.function3.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled=BHS_OTST552_phrase_selection[\n", " (\n", " (BHS_OTST552_phrase_selection['function3']=='Pred')\n", " | (BHS_OTST552_phrase_selection['function3']=='Subj')\n", " | (BHS_OTST552_phrase_selection['function3']=='Objc')\n", " | (BHS_OTST552_phrase_selection['function3']=='Cmpl')\n", " | (BHS_OTST552_phrase_selection['function3']=='PreO')\n", " | (BHS_OTST552_phrase_selection['function3']=='Nega')\n", " | (BHS_OTST552_phrase_selection['function3']=='PreS')\n", " | (BHS_OTST552_phrase_selection['function3']=='Voct')\n", " )\n", " # |\n", " # (\n", " # (BHS_OTST552_phrase_selection['kind2']=='NC')\n", " # & (BHS_OTST552_phrase_selection['function3'].astype(str).str.contains('PreC'))\n", " # )\n", " ]\n", "BHS_OTST552_phrase_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHS_OTST552_phrase_selection_sampled=BHS_OTST552_phrase_selection_sampled \\\n", " .groupby(['function3'\n", " ]) \\\n", " .sample(n=100, random_state=1, replace=True)\\\n", " .sort_values(['function3'\n", " ], \n", " ascending=True)\n", "BHS_OTST552_phrase_selection_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled.drop_duplicates(subset=\"bol_sequence_number_phrase4\", keep='first', inplace=True)\n", "BHS_OTST552_phrase_selection_sampled.head(20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST552 raw sampled data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "phrasefunctions= BHS_OTST552_phrase_selection_sampled['function3'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "phrasefunctions.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_phrase-function_OTST_552_Qualifier-Selection_filtered_v0.3.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling for OTST625" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_phrase-function_OTST_625_Qualifier-Selection_unfiltered_v0.3.tsv', delimiter='\\t', encoding='utf-16')\n", "BHS_OTST625_phrase_selection.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "vt=BHS_OTST625_phrase_selection.function3.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection_sampled=BHS_OTST625_phrase_selection[\n", " (\n", " (BHS_OTST625_phrase_selection['function3']=='Pred')\n", " | (BHS_OTST625_phrase_selection['function3']=='Subj')\n", " | (BHS_OTST625_phrase_selection['function3']=='Objc')\n", " | (BHS_OTST625_phrase_selection['function3']=='Cmpl')\n", " | (BHS_OTST625_phrase_selection['function3']=='PreO')\n", " | (BHS_OTST625_phrase_selection['function3']=='Nega')\n", " | (BHS_OTST625_phrase_selection['function3']=='PreS')\n", " | (BHS_OTST625_phrase_selection['function3']=='Voct')\n", " )\n", " |\n", " (\n", " (BHS_OTST625_phrase_selection['kind2']=='NC')\n", " & (BHS_OTST625_phrase_selection['function3'].astype(str).str.contains('PreC'))\n", " )\n", " ]\n", "BHS_OTST625_phrase_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHS_OTST625_phrase_selection_sampled=BHS_OTST625_phrase_selection_sampled \\\n", " .groupby(['function3'\n", " ]) \\\n", " .sample(n=100, random_state=1, replace=True)\\\n", " .sort_values(['function3'\n", " ], \n", " ascending=True)\n", "BHS_OTST625_phrase_selection_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection_sampled.drop_duplicates(subset=\"bol_sequence_number_phrase4\", keep='first', inplace=True)\n", "BHS_OTST625_phrase_selection_sampled.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection_sampled.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST625 raw sampled data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_phrase_selection_sampled.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "phrasefunctions= BHS_OTST625_phrase_selection_sampled['function3'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "phrasefunctions.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_phrase_selection_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_phrase-function_OTST_625_Qualifier-Selection_filtered_v0.3.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Syntax: Clause Relation Analysis" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Genesis\n" ] }, { "cell_type": "code", "execution_count": 165, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.45s 6299 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Genesis 1:1בְּרֵאשִׁ֖ית בָּרָ֣א אֱלֹהִ֑ים אֵ֥ת הַשָּׁמַ֖יִם וְאֵ֥ת הָאָֽרֶץ׃ בְּ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Genesis='''\n", "verse book=Genesis chapter=1|3|6|12|13|18|19|20|21|22|25|26|27 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Genesis = BHSa4c.search(Genesis)\n", "BHSa4c.table(Genesis, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Exodus\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 166, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.01s 363 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Exodus 20:1וַיְדַבֵּ֣ר אֱלֹהִ֔ים אֵ֛ת כָּל־הַדְּבָרִ֥ים הָאֵ֖לֶּה וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Exodus='''\n", "verse book=Exodus chapter=20 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Exodus = BHSa4c.search(Exodus)\n", "BHSa4c.table(Exodus, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Numeri\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 167, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 1.77s 46 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Numbers 6:22וַיְדַבֵּ֥ר יְהוָ֖ה אֶל־מֹשֶׁ֥ה וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Numeri='''\n", "verse book=Numeri chapter=6 verse=22|23|24|25|26|27\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Numeri = BHSa4c.search(Numeri)\n", "BHSa4c.table(Numeri, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Josua\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 168, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.07s 1194 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Joshua 1:1וַיְהִ֗י אַחֲרֵ֛י מֹ֥ות מֹשֶׁ֖ה עֶ֣בֶד יְהוָ֑ה וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Josua='''\n", "verse book=Josua chapter=1|10 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Josua = BHSa4c.search(Josua)\n", "BHSa4c.table(Josua, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Judices\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 169, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.13s 708 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Judges 19:1וַיְהִי֙ בַּיָּמִ֣ים הָהֵ֔ם וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Judices='''\n", "verse book=Judices chapter=19 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Judices = BHSa4c.search(Judices)\n", "BHSa4c.table(Judices, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Samuel_I\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 170, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.16s 467 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
11_Samuel 1:1וַיְהִי֩ אִ֨ישׁ אֶחָ֜ד מִן־הָרָמָתַ֛יִם צֹופִ֖ים מֵהַ֣ר אֶפְרָ֑יִם וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Samuel_I='''\n", "verse book=Samuel_I chapter=1 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "'''\n", "Samuel_I = BHSa4c.search(Samuel_I)\n", "BHSa4c.table(Samuel_I, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Reges_I\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 171, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.34s 512 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
11_Kings 21:1וַיְהִ֗י אַחַר֙ הַדְּבָרִ֣ים הָאֵ֔לֶּה וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Reges_I='''\n", "verse book=Reges_I chapter=21 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Reges_I = BHSa4c.search(Reges_I)\n", "BHSa4c.table(Reges_I, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Reges_II\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 172, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.08s 659 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
12_Kings 6:1וַיֹּאמְר֥וּ בְנֵֽי־הַנְּבִיאִ֖ים אֶל־אֱלִישָׁ֑ע וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Reges_II='''\n", "verse book=Reges_II chapter=6 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "\n", "\n", "'''\n", "Reges_II = BHSa4c.search(Reges_II)\n", "BHSa4c.table(Reges_II, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Jeremia\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 173, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 1.92s 1416 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Jeremiah 37:1וַיִּ֨מְלָךְ־מֶ֔לֶךְ צִדְקִיָּ֖הוּ בֶּן־יֹֽאשִׁיָּ֑הוּ תַּ֗חַת כָּנְיָ֨הוּ֙ בֶּן־יְהֹ֣ויָקִ֔ים וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Jeremia='''\n", "verse book=Jeremia chapter=37|38|39 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Jeremia = BHSa4c.search(Jeremia)\n", "BHSa4c.table(Jeremia, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Jona\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 174, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.10s 326 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Jonah 1:1וַֽיְהִי֙ דְּבַר־יְהוָ֔ה אֶל־יֹונָ֥ה בֶן־אֲמִתַּ֖י וַֽ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Jona='''\n", "verse book=Jona chapter=1 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Jona = BHSa4c.search(Jona)\n", "BHSa4c.table(Jona, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Psalmi\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 175, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.07s 130 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Psalms 1:1אַ֥שְֽׁרֵי־הָאִ֗ישׁ אַ֥שְֽׁרֵי־
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Psalmi='''\n", "verse book=Psalmi chapter=1|3 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Psalmi = BHSa4c.search(Psalmi)\n", "BHSa4c.table(Psalmi, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Clauses from Ruth\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 176, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.13s 1074 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Ruth 1:1וַיְהִ֗י בִּימֵי֙ וַ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Ruth='''\n", "verse book=Ruth chapter=1|2|3 verse*\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Ruth = BHSa4c.search(Ruth)\n", "BHSa4c.table(Ruth, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### Phrases from Isiah\n", "I need to add `clause kind=WP` so that I can also catch vocatives." ] }, { "cell_type": "code", "execution_count": 177, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.25s 111 results\n" ] }, { "data": { "text/html": [ "\n", "
npverseclauseword
1Isaiah 5:1אָשִׁ֤ירָה נָּא֙ לִֽידִידִ֔י שִׁירַ֥ת דֹּודִ֖י לְכַרְמֹ֑ו אָשִׁ֤ירָה
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Isiah='''\n", "verse book=Jesaia chapter=5 verse=1|2|3|4|5|6|7\n", " c1:clause typ* kind=NC|VC rela=Attr|Objc|NA domain*\n", " /without/\n", " word g_word_noaccent~^\\*\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " /without/\n", " :: word sp=art|subs|nmpr|advb|prep|conj|prps|prde|prin|intj|nega|inrg|adjv\n", " /-/\n", " word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num*\n", "\n", "'''\n", "Isiah = BHSa4c.search(Isiah)\n", "BHSa4c.table(Isiah, start=1, end=1, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Exporting" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST551 Export" ] }, { "cell_type": "code", "execution_count": 178, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Ruth, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_clause-relation_OTST_551_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST552 Export" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Psalmi+Ruth, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_clause-relation_OTST_552_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### OTST625 Export" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Genesis+Exodus+Numeri+Josua+Judices+Samuel_I+Reges_I+Reges_II+Jeremia+Jona+Psalmi+Ruth+Isiah, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='0_source_BHSa4c_BOL_syntax_clause-relation_OTST_625_Qualifier-Selection_unfiltered_v0.3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Export Reges_I 21:1-17" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(Reges_I, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/OTST551-2_exams_og/', toFile='OTST552_week12_midterm-sample_Reges21_clause-relation.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Sampling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling for OTST551" ] }, { "cell_type": "code", "execution_count": 182, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0.1Unnamed: 0RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3bol_lexeme_occurrences3bol_monad_num3bol_sequence_number_clause3bol_sequence_number_clause_atom3bol_sequence_number_phrase3bol_sequence_number_phrase_atom3SDATSAU_qualifier_selectionmanual exam selection
001116Genesis171414360verseוַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ...Genesis1427574clauseאֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַNNCAttrNmCl116wordאֲשֶׁ֖ר550011622236973cl-rela_attr-asherNaN
11176138Genesis181414361verseוַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ...Genesis1427579clauseיֹ֥ום שֵׁנִֽי׃ פNNCNaNNmCl138wordיֹ֥ום230413827288589cl-rela_independent-ncNaN
22140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
32140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
43143216Genesis1121414365verseוַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע...Genesis1427596clauseעֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּNVCAttrPtcp216wordעֹ֥שֶׂה26292164448137147cl-rela_attr-participleNaN
\n", "
" ], "text/plain": [ " Unnamed: 0.1 Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 \\\n", "0 0 1 116 Genesis 1 7 1414360 verse \n", "1 1 176 138 Genesis 1 8 1414361 verse \n", "2 2 140 189 Genesis 1 11 1414364 verse \n", "3 2 140 189 Genesis 1 11 1414364 verse \n", "4 3 143 216 Genesis 1 12 1414365 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ... Genesis 1 \n", "1 וַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ... Genesis 1 \n", "2 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "3 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "4 וַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע... Genesis 1 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 \\\n", "0 427574 clause אֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַ N NC Attr NmCl \n", "1 427579 clause יֹ֥ום שֵׁנִֽי׃ פ N NC NaN NmCl \n", "2 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "3 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "4 427596 clause עֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּ N VC Attr Ptcp \n", "\n", " NODE3 TYPE3 TEXT3 bol_lexeme_occurrences3 bol_monad_num3 \\\n", "0 116 word אֲשֶׁ֖ר 5500 116 \n", "1 138 word יֹ֥ום 2304 138 \n", "2 187 word מַזְרִ֣יעַ 56 187 \n", "3 187 word מַזְרִ֣יעַ 56 187 \n", "4 216 word עֹ֥שֶׂה 2629 216 \n", "\n", " bol_sequence_number_clause3 bol_sequence_number_clause_atom3 \\\n", "0 22 23 \n", "1 27 28 \n", "2 38 39 \n", "3 38 39 \n", "4 44 48 \n", "\n", " bol_sequence_number_phrase3 bol_sequence_number_phrase_atom3 \\\n", "0 69 73 \n", "1 85 89 \n", "2 118 124 \n", "3 118 124 \n", "4 137 147 \n", "\n", " SDATSAU_qualifier_selection manual exam selection \n", "0 cl-rela_attr-asher NaN \n", "1 cl-rela_independent-nc NaN \n", "2 cl-rela_attr-participle NaN \n", "3 cl-rela_attr-participle NaN \n", "4 cl-rela_attr-participle NaN " ] }, "execution_count": 182, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST551_clause_selection=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_clause-relation_OTST_551_Qualifier-Selection_filtered_v0.3.xlsx')\n", "BHS_OTST551_clause_selection.head()" ] }, { "cell_type": "code", "execution_count": 183, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 150 entries, 0 to 149\n", "Data columns (total 29 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0.1 150 non-null int64 \n", " 1 Unnamed: 0 150 non-null int64 \n", " 2 R 150 non-null int64 \n", " 3 S1 150 non-null object \n", " 4 S2 150 non-null int64 \n", " 5 S3 150 non-null int64 \n", " 6 NODE1 150 non-null int64 \n", " 7 TYPE1 150 non-null object \n", " 8 TEXT1 150 non-null object \n", " 9 book1 150 non-null object \n", " 10 chapter1 150 non-null int64 \n", " 11 NODE2 150 non-null int64 \n", " 12 TYPE2 150 non-null object \n", " 13 TEXT2 150 non-null object \n", " 14 domain2 150 non-null object \n", " 15 kind2 150 non-null object \n", " 16 rela2 90 non-null object \n", " 17 typ2 150 non-null object \n", " 18 NODE3 150 non-null int64 \n", " 19 TYPE3 150 non-null object \n", " 20 TEXT3 150 non-null object \n", " 21 bol_lexeme_occurrences3 150 non-null int64 \n", " 22 bol_monad_num3 150 non-null int64 \n", " 23 bol_sequence_number_clause3 150 non-null int64 \n", " 24 bol_sequence_number_clause_atom3 150 non-null int64 \n", " 25 bol_sequence_number_phrase3 150 non-null int64 \n", " 26 bol_sequence_number_phrase_atom3 150 non-null int64 \n", " 27 SDATSAU_qualifier_selection 150 non-null object \n", " 28 manual exam selection 0 non-null float64\n", "dtypes: float64(1), int64(15), object(13)\n", "memory usage: 34.1+ KB\n" ] } ], "source": [ "BHS_OTST551_clause_selection.info()" ] }, { "cell_type": "code", "execution_count": 184, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['cl-rela_attr-asher', 'cl-rela_independent-nc', 'cl-rela_attr-participle', 'cl-rela_objc', 'cl-rela_independent-vc']\n" ] } ], "source": [ "vt=BHS_OTST551_clause_selection.SDATSAU_qualifier_selection.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": 192, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 120 entries, 0 to 149\n", "Data columns (total 29 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0.1 120 non-null int64 \n", " 1 Unnamed: 0 120 non-null int64 \n", " 2 R 120 non-null int64 \n", " 3 S1 120 non-null object \n", " 4 S2 120 non-null int64 \n", " 5 S3 120 non-null int64 \n", " 6 NODE1 120 non-null int64 \n", " 7 TYPE1 120 non-null object \n", " 8 TEXT1 120 non-null object \n", " 9 book1 120 non-null object \n", " 10 chapter1 120 non-null int64 \n", " 11 NODE2 120 non-null int64 \n", " 12 TYPE2 120 non-null object \n", " 13 TEXT2 120 non-null object \n", " 14 domain2 120 non-null object \n", " 15 kind2 120 non-null object \n", " 16 rela2 60 non-null object \n", " 17 typ2 120 non-null object \n", " 18 NODE3 120 non-null int64 \n", " 19 TYPE3 120 non-null object \n", " 20 TEXT3 120 non-null object \n", " 21 bol_lexeme_occurrences3 120 non-null int64 \n", " 22 bol_monad_num3 120 non-null int64 \n", " 23 bol_sequence_number_clause3 120 non-null int64 \n", " 24 bol_sequence_number_clause_atom3 120 non-null int64 \n", " 25 bol_sequence_number_phrase3 120 non-null int64 \n", " 26 bol_sequence_number_phrase_atom3 120 non-null int64 \n", " 27 SDATSAU_qualifier_selection 120 non-null object \n", " 28 manual exam selection 0 non-null float64\n", "dtypes: float64(1), int64(15), object(13)\n", "memory usage: 28.1+ KB\n" ] } ], "source": [ "BHS_OTST551_clause_selection_sampled=BHS_OTST552_clause_selection[\n", " (~BHS_OTST551_clause_selection['SDATSAU_qualifier_selection'].astype(str).str.contains('objc'))\n", "\n", " ]\n", "BHS_OTST551_clause_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": 193, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0.1Unnamed: 0RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3bol_lexeme_occurrences3bol_monad_num3bol_sequence_number_clause3bol_sequence_number_clause_atom3bol_sequence_number_phrase3bol_sequence_number_phrase_atom3SDATSAU_qualifier_selectionmanual exam selection
001116Genesis171414360verseוַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ...Genesis1427574clauseאֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַNNCAttrNmCl116wordאֲשֶׁ֖ר550011622236973cl-rela_attr-asherNaN
11176138Genesis181414361verseוַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ...Genesis1427579clauseיֹ֥ום שֵׁנִֽי׃ פNNCNaNNmCl138wordיֹ֥ום230413827288589cl-rela_independent-ncNaN
32140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
22140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
22140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
55143216Genesis1121414365verseוַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע...Genesis1427596clauseעֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּNVCAttrPtcp216wordעֹ֥שֶׂה26292164448137147cl-rela_attr-participleNaN
1114147534Genesis1291414382verseוַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ...Genesis1427665clauseזֹרֵ֣עַ זֶ֗רַעQVCAttrPtcp599wordזֹרֵ֣עַ56599116122342358cl-rela_attr-participleNaN
1215148546Genesis1291414382verseוַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ...Genesis1427668clauseזֹרֵ֣עַ זָ֑רַעQVCAttrPtcp616wordזֹרֵ֣עַ56616119126349367cl-rela_attr-participleNaN
1315148546Genesis1291414382verseוַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ...Genesis1427668clauseזֹרֵ֣עַ זָ֑רַעQVCAttrPtcp616wordזֹרֵ֣עַ56616119126349367cl-rela_attr-participleNaN
1315148546Genesis1291414382verseוַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ...Genesis1427668clauseזֹרֵ֣עַ זָ֑רַעQVCAttrPtcp616wordזֹרֵ֣עַ56616119126349367cl-rela_attr-participleNaN
\n", "
" ], "text/plain": [ " Unnamed: 0.1 Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 \\\n", "0 0 1 116 Genesis 1 7 1414360 verse \n", "1 1 176 138 Genesis 1 8 1414361 verse \n", "3 2 140 189 Genesis 1 11 1414364 verse \n", "2 2 140 189 Genesis 1 11 1414364 verse \n", "2 2 140 189 Genesis 1 11 1414364 verse \n", "5 5 143 216 Genesis 1 12 1414365 verse \n", "11 14 147 534 Genesis 1 29 1414382 verse \n", "12 15 148 546 Genesis 1 29 1414382 verse \n", "13 15 148 546 Genesis 1 29 1414382 verse \n", "13 15 148 546 Genesis 1 29 1414382 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ... Genesis 1 \n", "1 וַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ... Genesis 1 \n", "3 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "2 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "2 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "5 וַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע... Genesis 1 \n", "11 וַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ... Genesis 1 \n", "12 וַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ... Genesis 1 \n", "13 וַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ... Genesis 1 \n", "13 וַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ... Genesis 1 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 \\\n", "0 427574 clause אֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַ N NC Attr NmCl \n", "1 427579 clause יֹ֥ום שֵׁנִֽי׃ פ N NC NaN NmCl \n", "3 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "2 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "2 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "5 427596 clause עֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּ N VC Attr Ptcp \n", "11 427665 clause זֹרֵ֣עַ זֶ֗רַע Q VC Attr Ptcp \n", "12 427668 clause זֹרֵ֣עַ זָ֑רַע Q VC Attr Ptcp \n", "13 427668 clause זֹרֵ֣עַ זָ֑רַע Q VC Attr Ptcp \n", "13 427668 clause זֹרֵ֣עַ זָ֑רַע Q VC Attr Ptcp \n", "\n", " NODE3 TYPE3 TEXT3 bol_lexeme_occurrences3 bol_monad_num3 \\\n", "0 116 word אֲשֶׁ֖ר 5500 116 \n", "1 138 word יֹ֥ום 2304 138 \n", "3 187 word מַזְרִ֣יעַ 56 187 \n", "2 187 word מַזְרִ֣יעַ 56 187 \n", "2 187 word מַזְרִ֣יעַ 56 187 \n", "5 216 word עֹ֥שֶׂה 2629 216 \n", "11 599 word זֹרֵ֣עַ 56 599 \n", "12 616 word זֹרֵ֣עַ 56 616 \n", "13 616 word זֹרֵ֣עַ 56 616 \n", "13 616 word זֹרֵ֣עַ 56 616 \n", "\n", " bol_sequence_number_clause3 bol_sequence_number_clause_atom3 \\\n", "0 22 23 \n", "1 27 28 \n", "3 38 39 \n", "2 38 39 \n", "2 38 39 \n", "5 44 48 \n", "11 116 122 \n", "12 119 126 \n", "13 119 126 \n", "13 119 126 \n", "\n", " bol_sequence_number_phrase3 bol_sequence_number_phrase_atom3 \\\n", "0 69 73 \n", "1 85 89 \n", "3 118 124 \n", "2 118 124 \n", "2 118 124 \n", "5 137 147 \n", "11 342 358 \n", "12 349 367 \n", "13 349 367 \n", "13 349 367 \n", "\n", " SDATSAU_qualifier_selection manual exam selection \n", "0 cl-rela_attr-asher NaN \n", "1 cl-rela_independent-nc NaN \n", "3 cl-rela_attr-participle NaN \n", "2 cl-rela_attr-participle NaN \n", "2 cl-rela_attr-participle NaN \n", "5 cl-rela_attr-participle NaN \n", "11 cl-rela_attr-participle NaN \n", "12 cl-rela_attr-participle NaN \n", "13 cl-rela_attr-participle NaN \n", "13 cl-rela_attr-participle NaN " ] }, "execution_count": 193, "metadata": {}, "output_type": "execute_result" } ], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHS_OTST551_clause_selection_sampled=BHS_OTST551_clause_selection_sampled \\\n", " .groupby(['SDATSAU_qualifier_selection'\n", " ]) \\\n", " .sample(n=30, random_state=1, replace=True)\\\n", " .sort_values(['bol_sequence_number_clause3'\n", " ], \n", " ascending=True)\n", "BHS_OTST551_clause_selection_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": 194, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0.1Unnamed: 0RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3bol_lexeme_occurrences3bol_monad_num3bol_sequence_number_clause3bol_sequence_number_clause_atom3bol_sequence_number_phrase3bol_sequence_number_phrase_atom3SDATSAU_qualifier_selectionmanual exam selection
001116Genesis171414360verseוַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ...Genesis1427574clauseאֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַNNCAttrNmCl116wordאֲשֶׁ֖ר550011622236973cl-rela_attr-asherNaN
11176138Genesis181414361verseוַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ...Genesis1427579clauseיֹ֥ום שֵׁנִֽי׃ פNNCNaNNmCl138wordיֹ֥ום230413827288589cl-rela_independent-ncNaN
32140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
55143216Genesis1121414365verseוַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע...Genesis1427596clauseעֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּNVCAttrPtcp216wordעֹ֥שֶׂה26292164448137147cl-rela_attr-participleNaN
1114147534Genesis1291414382verseוַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ...Genesis1427665clauseזֹרֵ֣עַ זֶ֗רַעQVCAttrPtcp599wordזֹרֵ֣עַ56599116122342358cl-rela_attr-participleNaN
\n", "
" ], "text/plain": [ " Unnamed: 0.1 Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 \\\n", "0 0 1 116 Genesis 1 7 1414360 verse \n", "1 1 176 138 Genesis 1 8 1414361 verse \n", "3 2 140 189 Genesis 1 11 1414364 verse \n", "5 5 143 216 Genesis 1 12 1414365 verse \n", "11 14 147 534 Genesis 1 29 1414382 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ... Genesis 1 \n", "1 וַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ... Genesis 1 \n", "3 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "5 וַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע... Genesis 1 \n", "11 וַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ... Genesis 1 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 \\\n", "0 427574 clause אֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַ N NC Attr NmCl \n", "1 427579 clause יֹ֥ום שֵׁנִֽי׃ פ N NC NaN NmCl \n", "3 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "5 427596 clause עֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּ N VC Attr Ptcp \n", "11 427665 clause זֹרֵ֣עַ זֶ֗רַע Q VC Attr Ptcp \n", "\n", " NODE3 TYPE3 TEXT3 bol_lexeme_occurrences3 bol_monad_num3 \\\n", "0 116 word אֲשֶׁ֖ר 5500 116 \n", "1 138 word יֹ֥ום 2304 138 \n", "3 187 word מַזְרִ֣יעַ 56 187 \n", "5 216 word עֹ֥שֶׂה 2629 216 \n", "11 599 word זֹרֵ֣עַ 56 599 \n", "\n", " bol_sequence_number_clause3 bol_sequence_number_clause_atom3 \\\n", "0 22 23 \n", "1 27 28 \n", "3 38 39 \n", "5 44 48 \n", "11 116 122 \n", "\n", " bol_sequence_number_phrase3 bol_sequence_number_phrase_atom3 \\\n", "0 69 73 \n", "1 85 89 \n", "3 118 124 \n", "5 137 147 \n", "11 342 358 \n", "\n", " SDATSAU_qualifier_selection manual exam selection \n", "0 cl-rela_attr-asher NaN \n", "1 cl-rela_independent-nc NaN \n", "3 cl-rela_attr-participle NaN \n", "5 cl-rela_attr-participle NaN \n", "11 cl-rela_attr-participle NaN " ] }, "execution_count": 194, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST551_clause_selection_sampled.drop_duplicates(subset=\"bol_sequence_number_clause3\", keep='first', inplace=True)\n", "BHS_OTST551_clause_selection_sampled.head(5)" ] }, { "cell_type": "code", "execution_count": 195, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 61 entries, 0 to 149\n", "Data columns (total 29 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0.1 61 non-null int64 \n", " 1 Unnamed: 0 61 non-null int64 \n", " 2 R 61 non-null int64 \n", " 3 S1 61 non-null object \n", " 4 S2 61 non-null int64 \n", " 5 S3 61 non-null int64 \n", " 6 NODE1 61 non-null int64 \n", " 7 TYPE1 61 non-null object \n", " 8 TEXT1 61 non-null object \n", " 9 book1 61 non-null object \n", " 10 chapter1 61 non-null int64 \n", " 11 NODE2 61 non-null int64 \n", " 12 TYPE2 61 non-null object \n", " 13 TEXT2 61 non-null object \n", " 14 domain2 61 non-null object \n", " 15 kind2 61 non-null object \n", " 16 rela2 29 non-null object \n", " 17 typ2 61 non-null object \n", " 18 NODE3 61 non-null int64 \n", " 19 TYPE3 61 non-null object \n", " 20 TEXT3 61 non-null object \n", " 21 bol_lexeme_occurrences3 61 non-null int64 \n", " 22 bol_monad_num3 61 non-null int64 \n", " 23 bol_sequence_number_clause3 61 non-null int64 \n", " 24 bol_sequence_number_clause_atom3 61 non-null int64 \n", " 25 bol_sequence_number_phrase3 61 non-null int64 \n", " 26 bol_sequence_number_phrase_atom3 61 non-null int64 \n", " 27 SDATSAU_qualifier_selection 61 non-null object \n", " 28 manual exam selection 0 non-null float64\n", "dtypes: float64(1), int64(15), object(13)\n", "memory usage: 14.3+ KB\n" ] } ], "source": [ "BHS_OTST551_clause_selection_sampled.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST551 raw sampled data" ] }, { "cell_type": "code", "execution_count": 196, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0.1Unnamed: 0RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3bol_lexeme_occurrences3bol_monad_num3bol_sequence_number_clause3bol_sequence_number_clause_atom3bol_sequence_number_phrase3bol_sequence_number_phrase_atom3SDATSAU_qualifier_selectionmanual exam selection
001116Genesis171414360verseוַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ...Genesis1427574clauseאֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַNNCAttrNmCl116wordאֲשֶׁ֖ר550011622236973cl-rela_attr-asherNaN
11176138Genesis181414361verseוַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ...Genesis1427579clauseיֹ֥ום שֵׁנִֽי׃ פNNCNaNNmCl138wordיֹ֥ום230413827288589cl-rela_independent-ncNaN
32140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
55143216Genesis1121414365verseוַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע...Genesis1427596clauseעֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּNVCAttrPtcp216wordעֹ֥שֶׂה26292164448137147cl-rela_attr-participleNaN
1114147534Genesis1291414382verseוַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ...Genesis1427665clauseזֹרֵ֣עַ זֶ֗רַעQVCAttrPtcp599wordזֹרֵ֣עַ56599116122342358cl-rela_attr-participleNaN
\n", "
" ], "text/plain": [ " Unnamed: 0.1 Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 \\\n", "0 0 1 116 Genesis 1 7 1414360 verse \n", "1 1 176 138 Genesis 1 8 1414361 verse \n", "3 2 140 189 Genesis 1 11 1414364 verse \n", "5 5 143 216 Genesis 1 12 1414365 verse \n", "11 14 147 534 Genesis 1 29 1414382 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ... Genesis 1 \n", "1 וַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ... Genesis 1 \n", "3 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "5 וַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע... Genesis 1 \n", "11 וַיֹּ֣אמֶר אֱלֹהִ֗ים הִנֵּה֩ נָתַ֨תִּי לָכֶ֜ם ... Genesis 1 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 \\\n", "0 427574 clause אֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַ N NC Attr NmCl \n", "1 427579 clause יֹ֥ום שֵׁנִֽי׃ פ N NC NaN NmCl \n", "3 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "5 427596 clause עֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּ N VC Attr Ptcp \n", "11 427665 clause זֹרֵ֣עַ זֶ֗רַע Q VC Attr Ptcp \n", "\n", " NODE3 TYPE3 TEXT3 bol_lexeme_occurrences3 bol_monad_num3 \\\n", "0 116 word אֲשֶׁ֖ר 5500 116 \n", "1 138 word יֹ֥ום 2304 138 \n", "3 187 word מַזְרִ֣יעַ 56 187 \n", "5 216 word עֹ֥שֶׂה 2629 216 \n", "11 599 word זֹרֵ֣עַ 56 599 \n", "\n", " bol_sequence_number_clause3 bol_sequence_number_clause_atom3 \\\n", "0 22 23 \n", "1 27 28 \n", "3 38 39 \n", "5 44 48 \n", "11 116 122 \n", "\n", " bol_sequence_number_phrase3 bol_sequence_number_phrase_atom3 \\\n", "0 69 73 \n", "1 85 89 \n", "3 118 124 \n", "5 137 147 \n", "11 342 358 \n", "\n", " SDATSAU_qualifier_selection manual exam selection \n", "0 cl-rela_attr-asher NaN \n", "1 cl-rela_independent-nc NaN \n", "3 cl-rela_attr-participle NaN \n", "5 cl-rela_attr-participle NaN \n", "11 cl-rela_attr-participle NaN " ] }, "execution_count": 196, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST551_clause_selection_sampled.head()" ] }, { "cell_type": "code", "execution_count": 197, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "clauserelatypes= BHS_OTST551_clause_selection_sampled['SDATSAU_qualifier_selection'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "clauserelatypes.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 191, "metadata": {}, "outputs": [], "source": [ "BHS_OTST551_clause_selection_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_clause-relation_OTST_551_Qualifier-Selection_filtered_v0.3.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling for OTST552" ] }, { "cell_type": "code", "execution_count": 179, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unnamed: 0.1Unnamed: 0RS1S2S3NODE1TYPE1TEXT1book1chapter1NODE2TYPE2TEXT2domain2kind2rela2typ2NODE3TYPE3TEXT3bol_lexeme_occurrences3bol_monad_num3bol_sequence_number_clause3bol_sequence_number_clause_atom3bol_sequence_number_phrase3bol_sequence_number_phrase_atom3SDATSAU_qualifier_selectionmanual exam selection
001116Genesis171414360verseוַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ...Genesis1427574clauseאֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַNNCAttrNmCl116wordאֲשֶׁ֖ר550011622236973cl-rela_attr-asherNaN
11176138Genesis181414361verseוַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ...Genesis1427579clauseיֹ֥ום שֵׁנִֽי׃ פNNCNaNNmCl138wordיֹ֥ום230413827288589cl-rela_independent-ncNaN
22140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
32140189Genesis1111414364verseוַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ...Genesis1427590clauseמַזְרִ֣יעַ זֶ֔רַעQVCAttrPtcp187wordמַזְרִ֣יעַ561873839118124cl-rela_attr-participleNaN
43143216Genesis1121414365verseוַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע...Genesis1427596clauseעֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּNVCAttrPtcp216wordעֹ֥שֶׂה26292164448137147cl-rela_attr-participleNaN
\n", "
" ], "text/plain": [ " Unnamed: 0.1 Unnamed: 0 R S1 S2 S3 NODE1 TYPE1 \\\n", "0 0 1 116 Genesis 1 7 1414360 verse \n", "1 1 176 138 Genesis 1 8 1414361 verse \n", "2 2 140 189 Genesis 1 11 1414364 verse \n", "3 2 140 189 Genesis 1 11 1414364 verse \n", "4 3 143 216 Genesis 1 12 1414365 verse \n", "\n", " TEXT1 book1 chapter1 \\\n", "0 וַיַּ֣עַשׂ אֱלֹהִים֮ אֶת־הָרָקִיעַ֒ וַיַּבְדֵּ... Genesis 1 \n", "1 וַיִּקְרָ֧א אֱלֹהִ֛ים לָֽרָקִ֖יעַ שָׁמָ֑יִם וַ... Genesis 1 \n", "2 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "3 וַיֹּ֣אמֶר אֱלֹהִ֗ים תַּֽדְשֵׁ֤א הָאָ֨רֶץ֙ דֶּ... Genesis 1 \n", "4 וַתֹּוצֵ֨א הָאָ֜רֶץ דֶּ֠שֶׁא עֵ֣שֶׂב מַזְרִ֤יע... Genesis 1 \n", "\n", " NODE2 TYPE2 TEXT2 domain2 kind2 rela2 typ2 \\\n", "0 427574 clause אֲשֶׁ֖ר מֵעַ֣ל לָרָקִ֑יעַ N NC Attr NmCl \n", "1 427579 clause יֹ֥ום שֵׁנִֽי׃ פ N NC NaN NmCl \n", "2 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "3 427590 clause מַזְרִ֣יעַ זֶ֔רַע Q VC Attr Ptcp \n", "4 427596 clause עֹ֥שֶׂה פְּרִ֛י לְמִינֵ֑הוּ N VC Attr Ptcp \n", "\n", " NODE3 TYPE3 TEXT3 bol_lexeme_occurrences3 bol_monad_num3 \\\n", "0 116 word אֲשֶׁ֖ר 5500 116 \n", "1 138 word יֹ֥ום 2304 138 \n", "2 187 word מַזְרִ֣יעַ 56 187 \n", "3 187 word מַזְרִ֣יעַ 56 187 \n", "4 216 word עֹ֥שֶׂה 2629 216 \n", "\n", " bol_sequence_number_clause3 bol_sequence_number_clause_atom3 \\\n", "0 22 23 \n", "1 27 28 \n", "2 38 39 \n", "3 38 39 \n", "4 44 48 \n", "\n", " bol_sequence_number_phrase3 bol_sequence_number_phrase_atom3 \\\n", "0 69 73 \n", "1 85 89 \n", "2 118 124 \n", "3 118 124 \n", "4 137 147 \n", "\n", " SDATSAU_qualifier_selection manual exam selection \n", "0 cl-rela_attr-asher NaN \n", "1 cl-rela_independent-nc NaN \n", "2 cl-rela_attr-participle NaN \n", "3 cl-rela_attr-participle NaN \n", "4 cl-rela_attr-participle NaN " ] }, "execution_count": 179, "metadata": {}, "output_type": "execute_result" } ], "source": [ "BHS_OTST552_clause_selection=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_clause-relation_OTST_552_Qualifier-Selection_filtered_v0.3.xlsx')\n", "BHS_OTST552_clause_selection.head()" ] }, { "cell_type": "code", "execution_count": 180, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 150 entries, 0 to 149\n", "Data columns (total 29 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Unnamed: 0.1 150 non-null int64 \n", " 1 Unnamed: 0 150 non-null int64 \n", " 2 R 150 non-null int64 \n", " 3 S1 150 non-null object \n", " 4 S2 150 non-null int64 \n", " 5 S3 150 non-null int64 \n", " 6 NODE1 150 non-null int64 \n", " 7 TYPE1 150 non-null object \n", " 8 TEXT1 150 non-null object \n", " 9 book1 150 non-null object \n", " 10 chapter1 150 non-null int64 \n", " 11 NODE2 150 non-null int64 \n", " 12 TYPE2 150 non-null object \n", " 13 TEXT2 150 non-null object \n", " 14 domain2 150 non-null object \n", " 15 kind2 150 non-null object \n", " 16 rela2 90 non-null object \n", " 17 typ2 150 non-null object \n", " 18 NODE3 150 non-null int64 \n", " 19 TYPE3 150 non-null object \n", " 20 TEXT3 150 non-null object \n", " 21 bol_lexeme_occurrences3 150 non-null int64 \n", " 22 bol_monad_num3 150 non-null int64 \n", " 23 bol_sequence_number_clause3 150 non-null int64 \n", " 24 bol_sequence_number_clause_atom3 150 non-null int64 \n", " 25 bol_sequence_number_phrase3 150 non-null int64 \n", " 26 bol_sequence_number_phrase_atom3 150 non-null int64 \n", " 27 SDATSAU_qualifier_selection 150 non-null object \n", " 28 manual exam selection 0 non-null float64\n", "dtypes: float64(1), int64(15), object(13)\n", "memory usage: 34.1+ KB\n" ] } ], "source": [ "BHS_OTST552_clause_selection.info()" ] }, { "cell_type": "code", "execution_count": 181, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['cl-rela_attr-asher', 'cl-rela_independent-nc', 'cl-rela_attr-participle', 'cl-rela_objc', 'cl-rela_independent-vc']\n" ] } ], "source": [ "vt=BHS_OTST552_clause_selection.SDATSAU_qualifier_selection.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_clause_selection_sampled=BHS_OTST552_clause_selection[\n", " (BHS_OTST552_clause_selection['SDATSAU_qualifier_selection'].astype(str).str.contains('cl'))\n", "\n", " ]\n", "BHS_OTST552_clause_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHS_OTST552_clause_selection_sampled=BHS_OTST552_clause_selection_sampled \\\n", " .groupby(['SDATSAU_qualifier_selection'\n", " ]) \\\n", " .sample(n=30, random_state=1, replace=True)\\\n", " .sort_values(['bol_sequence_number_clause3'\n", " ], \n", " ascending=True)\n", "BHS_OTST552_clause_selection_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_clause_selection_sampled.drop_duplicates(subset=\"bol_sequence_number_clause3\", keep='first', inplace=True)\n", "BHS_OTST552_clause_selection_sampled.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_clause_selection_sampled.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST552 raw sampled data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_clause_selection_sampled.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "clauserelatypes= BHS_OTST552_clause_selection_sampled['SDATSAU_qualifier_selection'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "clauserelatypes.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST552_clause_selection_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_clause-relation_OTST_552_Qualifier-Selection_filtered_v0.3.xlsx', encoding='utf-16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sampling for OTST625" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_clause-relation_OTST_625_Qualifier-Selection_unfiltered-annotated_v0.3.xlsx')\n", "BHS_OTST625_clause_selection.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "vt=BHS_OTST625_clause_selection.SDATSAU_qualifier_selection.unique().tolist()\n", "print(vt)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection_sampled=BHS_OTST625_clause_selection[\n", " (BHS_OTST625_clause_selection['SDATSAU_qualifier_selection'].astype(str).str.contains('cl'))\n", "\n", " ]\n", "BHS_OTST625_clause_selection_sampled.info()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "## A first attempt to organize and sample the data\n", "## We use `groupby`, a sequence of `sort_values`, and `nth` (to select only 2 entries per grouped category)\n", "\n", "BHS_OTST625_clause_selection_sampled=BHS_OTST625_clause_selection_sampled \\\n", " .groupby(['SDATSAU_qualifier_selection'\n", " ]) \\\n", " .sample(n=50, random_state=1, replace=True)\\\n", " .sort_values(['bol_sequence_number_clause3'\n", " ], \n", " ascending=True)\n", "BHS_OTST625_clause_selection_sampled.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection_sampled.drop_duplicates(subset=\"bol_sequence_number_clause3\", keep='first', inplace=True)\n", "BHS_OTST625_clause_selection_sampled.head(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection_sampled.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Inspecting the OTST625 raw sampled data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection_sampled.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "clauserelatypes= BHS_OTST625_clause_selection_sampled['SDATSAU_qualifier_selection'].value_counts()\n", "# Plotting the overall distribution\n", "plt.figure(figsize=(8, 5))\n", "clauserelatypes.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.title('Overall Tense Distribution')\n", "plt.xlabel('Part of Speech')\n", "plt.ylabel('Count')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHS_OTST625_clause_selection_sampled.to_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_BHSa4c_BOL_syntax_clause-relation_OTST_625_Qualifier-Selection_filtered_v0.3.xlsx', encoding='utf-16')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# OTST552 - Glanz course" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## OTST552 Exercise Materials" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Morphology Database" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#BibleOL_verbal_morphology=pd.read_csv('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "TotalMorphSelection=pd.read_excel('/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/0_source_OTST551_Heb-I-II-III_verbal-morphology_selection_of_2.xlsx', 'CourseApprovedForms')\n", "#BHSallWords=pd.read_csv('D:/OneDrive - Andrews University/1200_AUS-research/Fabric-TEXT/2_OTST551-2 Hebrew/BHSa4c_BOL_exercises.tsv', delimiter='\\t', encoding='utf-16')\n", "\n", "TotalMorphSelection.head(5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Week 10" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Morphology Master quiz" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "pd.set_option('display.max_columns', 100)\n", "OTST552_morph = TotalMorphSelection[(TotalMorphSelection[\"course approved\"]=='OTST551') | (TotalMorphSelection[\"course approved\"]=='OTST552')]\n", "OTST552_morph.head(10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Week10_morph=OTST552_morph.sample(n=10, replace=True, random_state=10).sort_values(['bol_monad_num1'],ascending=[True])\n", "OTST552_Week10_morph.head(20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "print(OTST552_Week10_morph[\"bol_monad_num1\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Week 11" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Morphology Master quiz" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "pd.set_option('display.max_columns', 100)\n", "OTST552_morph = TotalMorphSelection[(TotalMorphSelection[\"course approved\"]=='OTST551') | (TotalMorphSelection[\"course approved\"]=='OTST552')]\n", "OTST552_morph.head(2)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Week11_morph=OTST552_morph.sample(n=10, replace=True, random_state=12).sort_values(['bol_monad_num1'],ascending=[True])\n", "OTST552_Week11_morph.head(20)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(OTST552_Week11_morph[\"bol_monad_num1\"])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## OTST552 Exams" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### OTST552 Final (Hebrew II) - Vocab\n", "#### Text 01" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Vocab_Text01='''\n", "v1:verse book=Ruth chapter=1 verse=6|7\n", " w1:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences<1000 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", " w2:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences>100 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "w1 = w2\n", "\n", "'''\n", "OTST552_Final_Vocab_Text01 = BHSa4c.search(OTST552_Final_Vocab_Text01)\n", "BHSa4c.table(OTST552_Final_Vocab_Text01, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Vocab_Text01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_Vocab_Text01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 02" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Vocab_Text02='''\n", "v1:verse book=Psalmi chapter=3 verse=7|8\n", " w1:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences<1000 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", " w2:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences>100 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "w1 = w2\n", "\n", "'''\n", "OTST552_Final_Vocab_Text02 = BHSa4c.search(OTST552_Final_Vocab_Text02)\n", "BHSa4c.table(OTST552_Final_Vocab_Text02, start=1, end=4, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Vocab_Text02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_Vocab_Text02.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 03" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Vocab_Text03='''\n", "v1:verse book=Genesis chapter=26 verse=1|2|3|4|5|6\n", " w1:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences<1000 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", " w2:word bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences>100 bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "w1 = w2\n", "\n", "'''\n", "OTST552_Final_Vocab_Text03 = BHSa4c.search(OTST552_Final_Vocab_Text03)\n", "BHSa4c.table(OTST552_Final_Vocab_Text03, start=1, end=4, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Vocab_Text03, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_Vocab_Text03.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### OTST552 Final (Hebrew II) - Morphology" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Gen 19:1-20 (all texts used in class): " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text00_Gen19='''\n", "v1:verse book=Genesis chapter=19 verse=1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17|18|19|20\n", " clause\n", " word sp=verb bol_lexeme_occurrences* lex* bol_sequence_number_clause* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text00_Gen19 = BHSa4c.search(OTST552_Final_Morphology_Text00_Gen19)\n", "BHSa4c.table(OTST552_Final_Morphology_Text00_Gen19, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Morphology_Text00_Gen19, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text00_Gen19.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Gen 20 (all texts used in class): " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text00_Gen20='''\n", "v1:verse book=Genesis chapter=20\n", " clause\n", " word sp=verb bol_lexeme_occurrences* lex* bol_sequence_number_clause* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text00_Gen20 = BHSa4c.search(OTST552_Final_Morphology_Text00_Gen20)\n", "BHSa4c.table(OTST552_Final_Morphology_Text00_Gen20, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Morphology_Text00_Gen20, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text00_Gen20.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Ruth 1 (all texts used in class): " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text00_Ruth='''\n", "v1:verse book=Ruth chapter=1\n", " clause\n", " word sp=verb bol_lexeme_occurrences* lex* bol_sequence_number_clause* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text00_Ruth = BHSa4c.search(OTST552_Final_Morphology_Text00_Ruth)\n", "BHSa4c.table(OTST552_Final_Morphology_Text00_Ruth, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Morphology_Text00_Ruth, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text00_Ruth01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Psa 3 (all texts used in class): " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text00_Psalm3='''\n", "v1:verse book=Psalmi chapter=3\n", " clause\n", " word sp=verb bol_lexeme_occurrences* lex* bol_sequence_number_clause* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text00_Psalm3 = BHSa4c.search(OTST552_Final_Morphology_Text00_Psalm3)\n", "BHSa4c.table(OTST552_Final_Morphology_Text00_Psalm3, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Morphology_Text00_Psalm3, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text00_Psalm03.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 01" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text01='''\n", "v1:verse book=Ruth chapter=1 verse=6|7\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text01 = BHSa4c.search(OTST552_Final_Morphology_Text01)\n", "BHSa4c.table(OTST552_Final_Morphology_Text01, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_Morphology_Text01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 02" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text02='''\n", "v1:verse book=Psalmi chapter=3 verse=7|8\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text02 = BHSa4c.search(OTST552_Final_Morphology_Text02)\n", "BHSa4c.table(OTST552_Final_Morphology_Text02, start=1, end=4, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Morphology_Text02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text02.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 03" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552_Final_Morphology_Text03='''\n", "v1:verse book=Genesis chapter=26 verse=1|2|3|4|5|6\n", " word sp=verb bol_sequence_number_phrase* bol_sequence_number_phrase_atom* bol_lexeme_occurrences* bol_sequence_number_clause* bol_sequence_number_clause_atom* bol_monad_num* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552_Final_Morphology_Text03 = BHSa4c.search(OTST552_Final_Morphology_Text03)\n", "BHSa4c.table(OTST552_Final_Morphology_Text03, start=1, end=4, extraFeatures={'number'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552_Final_Morphology_Text03, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_VerbalMorphology_Text03.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### OTST552 Final (Hebrew II) - Phrase Function" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Gen 19:1-20 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text00_Gen19='''\n", "v1:verse book=Genesis chapter=19 verse=1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17|18|19|20\n", " clause typ*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text00_Gen19 = BHSa4c.search(OTST552Final_PhraseFunction_Text00_Gen19)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text00_Gen19, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text00_Gen19, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text00_Gen19.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Gen 20 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text00_Gen20='''\n", "v1:verse book=Genesis chapter=20\n", " clause typ*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text00_Gen20 = BHSa4c.search(OTST552Final_PhraseFunction_Text00_Gen20)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text00_Gen20, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text00_Gen20, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text00_Gen20.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Ruth 1 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text00_Ruth1='''\n", "v1:verse book=Ruth chapter=1\n", " clause typ*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text00_Ruth1 = BHSa4c.search(OTST552Final_PhraseFunction_Text00_Ruth1)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text00_Ruth1, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text00_Ruth1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text00_Ruth01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Psalm 3 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text00_Psalm3='''\n", "v1:verse book=Psalmi chapter=3\n", " clause typ*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text00_Psalm3 = BHSa4c.search(OTST552Final_PhraseFunction_Text00_Psalm3)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text00_Psalm3, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text00_Psalm3, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text00_Psalm3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sample Foreign Text" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_ForeignSample='''\n", "v1:verse book=Samuel_II chapter=7 verse=25|26\n", "/without/\n", " word bol_lexeme_occurrences<100\n", "/-/\n", " clause\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "\n", "'''\n", "OTST552Final_PhraseFunction_ForeignSample = BHSa4c.search(OTST552Final_PhraseFunction_ForeignSample)\n", "BHSa4c.show(OTST552Final_PhraseFunction_ForeignSample, start=1, end=40, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_ForeignSample, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_phrase-syntax_Heb-II_Final_PhraseFunction_ForeignSample.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 01 (Ruth 1)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text01='''\n", "v1:verse book=Ruth chapter=1 verse=6|7\n", " clause\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text01 = BHSa4c.search(OTST552Final_PhraseFunction_Text01)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text01, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 02 (Psalm 3)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text02='''\n", "v1:verse book=Psalmi chapter=3 verse=7|8\n", " clause\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "'''\n", "OTST552Final_PhraseFunction_Text02 = BHSa4c.search(OTST552Final_PhraseFunction_Text02)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text02, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text02.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 03" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text03='''\n", "v1:verse book=Genesis chapter=26 verse=1|2|3|4|5|6\n", " clause typ*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text03 = BHSa4c.search(OTST552Final_PhraseFunction_Text03)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text03, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text03, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text03.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 04" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text04='''\n", "v1:verse book=Genesis chapter=17 verse=1|2|3|4|5|6\n", " clause\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text04 = BHSa4c.search(OTST552Final_PhraseFunction_Text04)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text04, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text04, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text04.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 05" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_PhraseFunction_Text05='''\n", "v1:verse book=Samuel_I chapter=1\n", " clause typ\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " phrase function=Pred|Subj|Objc|Cmpl|PreC|PreO|PreS typ* det*\n", " word bol_sequence_number_phrase* bol_monad_num* lex*\n", "\n", "'''\n", "OTST552Final_PhraseFunction_Text05 = BHSa4c.search(OTST552Final_PhraseFunction_Text05)\n", "BHSa4c.table(OTST552Final_PhraseFunction_Text05, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_Text05, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_PhraseFunction_Text05.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "### OTST552 Final (Hebrew II) - Clause Relation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Gen 19:1-20 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text00_Gen19='''\n", "v1:verse book=Genesis chapter=19 verse=1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17|18|19|20\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text00_Gen19 = BHSa4c.search(OTST552Final_ClauseRelation_Text00_Gen19)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text00_Gen19, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text00_Gen19, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text00_Gen19.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Gen 20 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text00_Gen20='''\n", "v1:verse book=Genesis chapter=20\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text00_Gen20 = BHSa4c.search(OTST552Final_ClauseRelation_Text00_Gen20)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text00_Gen20, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text00_Gen20, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text00_Gen20.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Ruth 1 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text00_Ruth1='''\n", "v1:verse book=Ruth chapter=1\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text00_Ruth1 = BHSa4c.search(OTST552Final_ClauseRelation_Text00_Ruth1)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text00_Ruth1, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text00_Ruth1, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text00_Ruth1.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 00: Psalm 3 (all texts used in class):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text00_Psalm3='''\n", "v1:verse book=Psalmi chapter=3\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text00_Psalm3 = BHSa4c.search(OTST552Final_ClauseRelation_Text00_Psalm3)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text00_Psalm3, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text00_Psalm3, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text00_Psalm3.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sample Foreign Text" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_ForeignSample='''\n", "v1:verse book=Samuel_II chapter=7 verse=25|26\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "\n", "'''\n", "OTST552Final_ClauseRelation_ForeignSample = BHSa4c.search(OTST552Final_ClauseRelation_ForeignSample)\n", "BHSa4c.show(OTST552Final_ClauseRelation_ForeignSample, start=1, end=40, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_PhraseFunction_ForeignSample, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_ForeignSample.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 01" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text01='''\n", "v1:verse book=Ruth chapter=1 verse=6|7\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text01 = BHSa4c.search(OTST552Final_ClauseRelation_Text01)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text01, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text01, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text01.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 02" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text02='''\n", "v1:verse book=Psalmi chapter=3 verse=7|8\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text02 = BHSa4c.search(OTST552Final_ClauseRelation_Text02)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text02, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text02, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text02.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Text 03" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text03='''\n", "v1:verse book=Genesis chapter=26 verse=1|2|3|4|5|6\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text03 = BHSa4c.search(OTST552Final_ClauseRelation_Text03)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text03, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text03, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text03.tsv')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Text 04" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text04='''\n", "v1:verse book=Genesis chapter=17 verse=1|2|3|4|5|6\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text04 = BHSa4c.search(OTST552Final_ClauseRelation_Text04)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text04, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text04, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text04.tsv')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "#### Text 05" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "OTST552Final_ClauseRelation_Text05='''\n", "v1:verse book=Samuel_I chapter=1\n", " clause typ* kind* rela=NA|Attr|Objc domain*\n", " /without/\n", " word bol_qere_presence=1\n", " /-/\n", " /without/\n", " word language=Aramaic\n", " /-/\n", " /without/\n", " word bol_dict_vc~^four.*verb\n", " /-/\n", " word bol_sequence_number_clause* bol_dict_vc*\n", "\n", "'''\n", "OTST552Final_ClauseRelation_Text05 = BHSa4c.search(OTST552Final_ClauseRelation_Text05)\n", "BHSa4c.table(OTST552Final_ClauseRelation_Text05, start=1, end=5, extraFeatures={'number'}, condensed=True, colorMap={13: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "BHSa4c.export(OTST552Final_ClauseRelation_Text05, toDir='/Users/oliverglanz/Library/CloudStorage/OneDrive-AndrewsUniversity/1200_AUS-research/Fabric-TEXT/2_OTST551-2_Hebrew/BOL_exercises/', toFile='BHSa4c_BOL_Heb-II_Final_ClauseRelation_Text05.tsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Experiments" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Experiment01='''\n", "sentence\n", "/without/\n", " word bol_lexeme_occurrences<200\n", "/-/\n", "/without/\n", " word bol_dict_vc#regular\n", "/-/\n", "\n", "\n", "'''\n", "Experiment01 = BHSa4c.search(Experiment01)\n", "BHSa4c.show(Experiment01, start=1, end=5, extraFeatures={'number','bol_lexeme_occurrences'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Random Searches" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Experiment01='''\n", "word g_word~T:CAQ.: bol_monad_num\n", "\n", "\n", "\n", "\n", "'''\n", "Experiment01 = BHSa4c.search(Experiment01)\n", "BHSa4c.show(Experiment01, start=1, end=5, extraFeatures={'number','bol_lexeme_occurrences'}, condensed=False, colorMap={1: 'cyan'})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.9" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": { "height": "calc(100% - 180px)", "left": "10px", "top": "150px", "width": "352px" }, "toc_section_display": true, "toc_window_display": true }, "toc-autonumbering": true }, "nbformat": 4, "nbformat_minor": 4 }