{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Parts of Speech" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook introduces the concept of part-of-speech tagging as an additional way of processing texts. It's part of the [The Art of Literary Text Analysis](ArtOfLiteraryTextAnalysis.ipynb) (and assumes that you've already worked through previous notebooks – see the table of contents). In this notebook we'll look in particular at:\n", "\n", "* [What's a part-of-speech?](#What's-a-Part-of-Speech?)\n", "* [Examining frequencies and distribution for a specific part-of-speech](#Examining-Frequencies-and-Distribution-for-a-Specific-Part-of-Speech)\n", "* [Overall frequencies of parts of speech](#Overall-Frequencies-of-Parts-of-Speech)\n", "* [Word frequencies by part-of-speech](#Word-Frequencies-by-Part-of-Speech)\n", "* [Comparing parts of speech across texts](#Comparing-Parts-of-Speech-across-Texts)\n", "\n", "This notebook assumes you've saved a _The Gold Bug_ into a plain text file, as described in [Getting Texts](GettingTexts.ipynb). If that's not the case, you may wish to include the following:\n", "\n", "```python\n", "import urllib.request\n", "# retrieve Poe plain text value\n", "poeUrl = \"http://www.gutenberg.org/cache/epub/2147/pg2147.txt\"\n", "poeString = urllib.request.urlopen(poeUrl).read().decode()```\n", "\n", "And then this, in a separate cell so that we don't read repeatedly from Gutenberg:\n", "\n", "```python\n", "import os\n", "# isolate The Gold Bug\n", "start = poeString.find(\"THE GOLD-BUG\")\n", "end = poeString.find(\"FOUR BEASTS IN ONE\")\n", "goldBugString = poeString[start:end]\n", "# save the file locally\n", "directory = \"data\"\n", "if not os.path.exists(directory):\n", " os.makedirs(directory)\n", "with open(\"data/goldBug.txt\", \"w\") as f:\n", " f.write(goldBugString)```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What's a Part of Speech?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've already examined several ways of transforming and mapping words in a text:\n", "\n", "* Case manipulation: BUG, Bug, bug => bug\n", "* Stemming & lemmatization (bug, bugs => bug)\n", "* Word sense grouping (bug, beetle => bugword)\n", "\n", "Another tool at our disposal is to try to determine the part-of-speech of words in a text. [Parts of speech](http://en.wikipedia.org/wiki/Part_of_speech) are linguistic categories that identify the syntactic function of words, such as determiners (or articles), nouns, verbs, adjectives, prepositions, etc. Imagine, for instance, that we could determine that Text A has more adjectives per total number of words than Text B – might that allow us to speculate that Text A is more descriptive than Text B?\n", "\n", "Let's first look at the mechanics of identifying – or tagging – parts of speech in our text. We'll begin by reading in our _Gold Bug_ text and tokenizing it." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import nltk\n", "# read Gold Bug plain text into string\n", "with open(\"data/goldBug.txt\", \"r\") as f:\n", " goldBugString = f.read()\n", "goldBugTokens = nltk.word_tokenize(goldBugString) # tokenize the words (without transformation)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Consistent with other first encounters in this guide, we'll initially use the simplest syntax possible to tag the parts of speech in our tokens list, namely calling ```nltk.pos_tag()``` with our list of tokens as an argument. " ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "goldBugTagged = nltk.pos_tag(goldBugTokens)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(Some people have reported problems with Windows and Anaconda, related to character encoding issues in NLTK – here's [one possible solution](http://stackoverflow.com/questions/25590089/nltk-3-pos-tag-throws-unicodedecodeerror).)\n", "\n", "Tagging this way is an \"expensive\" operation, which is a computer programming way of saying that it's an intensive process that takes time and resources (like URL fetching, we want to do it as infrequently as possible). Behind the scenes, NLTK is loading a large dataset that it's using to help improve the tagging results.\n", "\n", "Let's take a peek at the first 22 token-tag pairs:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('THE', 'DT'),\n", " ('GOLD-BUG', 'NNP'),\n", " ('What', 'WP'),\n", " ('ho', 'NN'),\n", " ('!', '.'),\n", " ('what', 'WP'),\n", " ('ho', 'NN'),\n", " ('!', '.'),\n", " ('this', 'DT'),\n", " ('fellow', 'NN'),\n", " ('is', 'VBZ'),\n", " ('dancing', 'VBG'),\n", " ('mad', 'JJ'),\n", " ('!', '.'),\n", " ('He', 'PRP'),\n", " ('hath', 'VBD'),\n", " ('been', 'VBN'),\n", " ('bitten', 'VBN'),\n", " ('by', 'IN'),\n", " ('the', 'DT'),\n", " ('Tarantula', 'NNP'),\n", " ('.', '.')]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "goldBugTagged[:22]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see here a list of tuples with each tuple being composed of a token from the text and a code representing the part-of-speech. The codes are listed at the [Penn Treebank Project](http://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html) and includes the following:\n", "\n", "* DT: determiner (the, a…)\n", "* IN: preposition (to, from, …)\n", "* JJ: adjective (big, smart…)\n", "* NN: noun (car, school…)\n", "* NNP: proper noun (Montreal, Jill…)\n", "* PRP: personal pronoun (she, I…)\n", "* RB: adverb (freely, calmly…)\n", "* VBD, VBG, VBN, VBZ: verbs (dancing, said, been, is…)\n", "* WP: wh-pronoun (who, what…)\n", "\n", "Looking back at our initial list, we can see there are some correct tags, but others that seem dubious. For instance, _GOLD-BUG_ is incorrectly tagged as an adjective (short titles are difficult to parse) and _hath_ is tagged as a noun (archaic forms are also difficult).\n", "\n", "It's worth reiterating that the computer doesn't understand anything about the language being used, it's making a statistical guess based on the training set that it's already seen. In other words, based on a corpus of eclectic texts (including the [Brown Corpus])(http://en.wikipedia.org/wiki/Brown_Corpus), the part-of-speech tagger we're using is identifying certain words as, say, determiners, because that's how they were tagged previously. Some words can be a different part-of-speech depending on context (dance as a verb or dance as a noun), and the tagging may depend on words that precede or follow. Some words it simply won't recognize and may just guess at depending on the adjacent tags (or a default tag).\n", "\n", "For relatively normal modern English texts we can expect an accuracy of about 85-90%, which is far from perfect, but which does allow us to explore the texts in new ways." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Examining Frequencies and Distribution for a Specific Part of Speech" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true }, "outputs": [], "source": [ "goldBugAdjectives = [token for token, pos in goldBugTagged if \"JJ\" == pos]\n", "goldBugAdjectivesFreqs = nltk.FreqDist(goldBugAdjectives)\n", "goldBugAdjectivesFreqs.plot(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This might lead us to explore how some apparent opposite terms are used, such as \"first\" and \"last\", \"old\" and \"new\", \"few\" and \"many\", \"large\" and \"little\"." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another potentially useful part-of-speech to consider is proper names (NNP for singular and NNPS for plural)." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true }, "outputs": [], "source": [ "goldBugProperNouns = [token for token, pos in goldBugTagged if \"NNP\" in pos]\n", "nltk.FreqDist(goldBugProperNouns).plot(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once again we see some noisy (inaccurate) results, but some of these words may warrant a closer look." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "goldBugText = nltk.Text(goldBugTokens)\n", "goldBugText.dispersion_plot([\"Jupiter\",\"Legrand\",\"Jup\",\"Kidd\",\"Charleston\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Overall Frequencies of Parts of Speech" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've looked at adjectives and proper nouns, but each part of speech might lead us to some insights, and it might be valuable to look at the overall tag frequencies:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " NN IN DT , PRP JJ RB VBD . VB CC NNS VBN : TO NNP '' PRP$ VBP `` VBG CD MD VBZ FW \n", "2172 1814 1579 1302 1122 945 824 814 717 534 526 441 383 348 329 316 270 264 254 248 213 207 175 171 114 \n" ] }, { "data": { "image/png": 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e7x1J9xKUZgNxOVv+0rQCzgY6qGqrLGLU94sHWfZtishluKF35yVq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\njEnr/wHaGi29oQ36NQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "goldBugTags = [pos for word, pos in goldBugTagged]\n", "goldBugTagsFreqs = nltk.FreqDist(goldBugTags)\n", "goldBugTagsFreqs.tabulate(25)\n", "goldBugTagsFreqs.plot(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The graph isn't quite the usual fit for Zipf's Law (which we saw when looking at the most frequent terms in the text), but it's still pretty close. In other words, even frequency of parts of speech follow a similar trend.\n", "\n", "There are some part-of-speech categories that could be grouped together. For instance, we might want to consider all punctuation as the same (instead of separate tags for end-of-sentence and mid-sentence punctuation)." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " . NN IN DT PRP JJ RB VBD VB CC NNS VBN TO NNP VBP VBG CD MD VBZ FW \n", "3201 2172 1814 1579 1122 945 824 814 534 526 441 383 329 316 254 213 207 175 171 114 \n" ] } ], "source": [ "goldBugTagsNormalizedPunctuation = [pos if pos.isalpha() else \".\" for pos in goldBugTags]\n", "nltk.FreqDist(goldBugTagsNormalizedPunctuation).tabulate(20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Many of the tags have a third letter to specify a subcategory of tag, but we could keep just the first two letters to have more general categories. As such VB, VBD, VBP, VBG and VBZ would all be simply VB." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " . NN VB IN DT PR JJ RB CC TO CD MD FW WR WD WP PO RP EX PD UH \n", "3201 2930 2369 1814 1579 1122 1009 855 526 329 207 175 114 106 96 79 62 51 35 14 13 \n" ] } ], "source": [ "goldBugTagsNormalized = [pos[0:2] if pos.isalpha() else \".\" for pos in goldBugTags]\n", "goldBugTagsNormalizedFreqs = nltk.FreqDist(goldBugTagsNormalized)\n", "goldBugTagsNormalizedFreqs.tabulate(25)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We could also look at the distribution of parts of speech using our normalized tags." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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mjaaxdrL0xXTP6hG3VVY3i6/Ertn0FjabqWQAeAlwf5lpxzwTuNwD20sNAOXI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\nOUHxAcBxHOcE5f8HlNakLU+IfJMAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "nltk.Text(goldBugTagsNormalized).dispersion_plot(list(goldBugTagsNormalizedFreqs.keys()))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There may be a variety of things to further examine here, but one curious artefact is an apparent gap in all but the top (punctuation) line at about the 13,000 word offset marker (about four fifth of the way across). With a bit of tweaking we can get closer to the specific token." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[('and', 'CC'), ('the', 'DT'), ('goat', 'NN'), (':', ':'), ('``', '``'), ('53‡‡†305', 'CD'), (')', ')'), (')', ')'), ('6*', 'CD'), (';', ':'), ('4826', 'CD'), (')', ')'), ('4‡', 'CD'), (')', ')'), ('4‡', 'CD'), (')', ')'), (';', ':'), ('806*', 'CD'), (';', ':'), ('48†8¶60', 'CD'), (')', ')'), (')', ')'), ('85', 'CD'), (';', ':'), ('1‡', 'CD'), (')', ')'), (';', ':'), (':', ':'), ('‡', 'NN'), ('*8†83', 'NNP'), ('(', '('), ('88', 'CD'), (')', ')'), ('5*†', 'CD'), (';', ':'), ('46', 'CD'), ('(', '('), (';', ':'), ('88*96*', 'CD'), ('?', '.'), (';', ':'), ('8', 'CD'), (')', ')'), ('*‡', 'NN'), ('(', '('), (';', ':'), ('485', 'CD'), (')', ')'), (';', ':'), ('5*†2', 'CD'), (':', ':'), ('*‡', 'NN'), ('(', '('), (';', ':'), ('4956*', 'CD'), ('2', 'CD'), ('(', '('), ('5*', 'CD'), ('--', ':'), ('4', 'CD'), (')', ')'), ('8¶8*', 'CD'), (';', ':'), ('4069285', 'CD'), (')', ')'), (';', ':'), (')', ')'), ('6†8', 'CD'), (')', ')'), ('4‡‡', 'CD'), (';', ':'), ('1', 'CD'), ('(', '('), ('‡9', 'NN'), (';', ':'), ('48081', 'CD'), (';', ':'), ('8:8‡1', 'CD'), (';', ':'), ('4', 'CD'), ('8†85', 'CD'), (';', ':'), ('4', 'CD'), (')', ')'), ('485†528806*81', 'CD'), ('(', '('), ('‡9', 'NN'), (';', ':'), ('48', 'CD'), (';', ':'), ('(', '('), ('88', 'CD'), (';', ':'), ('4', 'CD'), ('(', '('), ('‡', 'VB'), ('?', '.'), ('34', 'CD'), (';', ':'), ('48', 'CD'), (')', ')'), ('4‡', 'CD'), (';', ':'), ('161', 'CD'), (';', ':'), (':', ':'), ('188', 'CD'), (';', ':'), ('‡', 'NNP'), ('?', '.'), (';', ':'), (\"''\", \"''\"), (\"''\", \"''\"), ('But', 'CC'), (',', ','), (\"''\", \"''\"), ('said', 'VBD'), ('I', 'PRP'), (',', ','), ('returning', 'VBG'), ('him', 'PRP'), ('the', 'DT'), ('slip', 'NN'), (',', ','), ('``', '``'), ('I', 'PRP'), ('am', 'VBP'), ('as', 'RB'), ('much', 'JJ'), ('in', 'IN'), ('the', 'DT'), ('dark', 'NN'), ('as', 'IN'), ('ever', 'RB'), ('.', '.')]\n" ] } ], "source": [ "print(goldBugTagged[12900:13035])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From reading the text we may recognize this as one of the moments with encrypted text with a lot of punctuation, digits and other non alphabetic characters. We could even search for \"the goat:\" and show some of the text following it to see the string in context." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "nspection. The following characters were rudely traced, in a red\n", "tint, between the death's-head and the goat:\n", "\n", " \"53‡‡†305))6*;4826)4‡)4‡);806*;48†8¶60))85;1‡);:‡\n", " *8†83(88)5*†;46(;88*96*?;8)*‡(;485);5*†2:*‡(;4956*\n", " 2(5*--4)8¶8*;4069285);)6†8)4‡‡;1(‡9;48081;8:8‡1;4\n", " 8†85;4)485†528806*81(‡9;48;(88;4(‡?34;48)4‡;161;:\n", " 188;‡?;\"\n", "\n", "\"But,\" said I, returning him the slip, \"I am as much in the dark as\n", "\n" ] } ], "source": [ "theGoat = goldBugString.find(\"the goat:\")\n", "print(goldBugString[theGoat-100:theGoat+300])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We knew that _The Gold Bug_ text has some peculiarities, but it's also reassuring to see that some fairly simple experiments with parts-of-speech allowed us to identify one of the unusual aspects of the text, namely, the encrypted code." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Word Frequencies by Part of Speech" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It might also be interesting to see what the top frequency terms are for each part-of-speech category. To do this we'll need to go back to the tagged list that includes both words and pos, but we'll normalize the pos as we've done above." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'goldBugTagged' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgoldBugTaggedNormalized\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mword\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misalpha\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;34m\".\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mword\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mgoldBugTagged\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mNameError\u001b[0m: name 'goldBugTagged' is not defined" ] } ], "source": [ "goldBugTaggedNormalized = [(word, pos[0:2] if pos.isalpha() else \".\") for word, pos in goldBugTagged]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see what parts-of speech are contained in this list:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "21\n" ] } ], "source": [ "goldBugTagsNormalized = set([pos for word, pos in goldBugTaggedNormalized]) # get unique pos tags\n", "print(len(goldBugTagsNormalized))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Instead of looking at all parts-of-speech, we could further refine our list to cases where there are more than two different words in the category. To do this we'll need to build a frequency list and keep track of any categories that have two or fewer words. We'll also skip punctuation." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['IN', 'CC', 'PO', 'VB', 'MD', 'WR', 'WD', 'EX', 'NN', 'RP', 'CD', 'JJ', 'PR', 'PD', 'WP', 'DT', 'RB', 'FW']\n" ] } ], "source": [ "goldBugTagsNormalizedAndFiltered = []\n", "for currentpos in goldBugTagsNormalized:\n", " freqs = nltk.FreqDist([word.lower() for word, pos in goldBugTaggedNormalized if currentpos == pos])\n", " if len(freqs)>2 and currentpos != \".\":\n", " goldBugTagsNormalizedAndFiltered.append(currentpos)\n", "print(goldBugTagsNormalizedAndFiltered) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We could simply loop through each tag and create a graph of the top frequency terms, something like this:\n", "\n", "```python\n", "for currentpos in goldBugTagsNormalizedAndFiltered:\n", " words = [word for word, pos in goldBugTaggedNormalized if pos == currentpos]\n", " freqs = nltk.FreqDist(words)\n", " freqs.plot(20, title=currentpos)```\n", "\n", "But that would take up a lot of space vertically in our notebook, which means more scrolling, but also potentially more difficult to compare different graphs.\n", "\n", "What we can do instead is to use [matplotlib.pyplot.subplot()](http://matplotlib.org/api/pyplot_api.html?highlight=subplot#matplotlib.pyplot.subplot) to draw a grid. We can set the number of rows and columns by hand or we can set them programmatically depending on the content we have. Let's first determine how many pos tags we have." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "18" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(goldBugTagsNormalizedAndFiltered)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, assuming we want three columns of graphs, now we need to calculate how many rows we need, which is esentially 14/3 plus one row for any remainder. The way to calculate that in Python is with the [math.ceil()](https://docs.python.org/3.4/library/math.html#math.ceil) function, which rounds a decimal number up to the next integer." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import math\n", "\n", "goldBugTagsGridRows = math.ceil(len(goldBugTagsNormalizedAndFiltered)/3) # the number of rows we need\n", "goldBugTagsGridRows # 4 rows of 3 plus 1 row of 2 = 5 rows, 14 cells" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let's build our grid of graphs with subplot." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "image/png": 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SQESMIheNLk0pXVnZvTYi9kgprYmIScBTlf2PA9O6HT61su8NFixY8Np2W1sb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QoY0/kos4EkKIWkMRR6LT3Hcf7LRT/F122aytEaJrU00jyZ1BfqJycY9UtaFD4YwzsrZGiNpD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TI0wj10hTLkcQ+HHKJcR+efn18ZOoOO8DhaFnjD3d929wnAVcCQDrhOt6crVojOJp6BiOcg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\n39KJJNWynqgTNdM4euQR2HlnGDeuh0JJUhVolAFBRMwNPAMsnVKa5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kxJKZ3Y8vO1wMiU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vIMhaRzVHd6uXX9Vxnr1cn0gGMU8ls/K+DHwgaenyvbyEDBidAlwYEd8gA0JHSFqjannP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Kv3aM5JdcM7I8HxIiRsLYcY8O/Zw9UbLahfLjeATbvxMsSWvbcbWqD2s4lS1rIbnHd1xCreYK/7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\n7yB5ori64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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "fig, axes = plt.subplots(goldBugTagsGridRows, 3, figsize=(20, 30)) # define the number of row, columns, and overall size\n", "for idx, currentpos in enumerate(goldBugTagsNormalizedAndFiltered): # this gives us an indexed enumeration \n", " words = [word.lower() for word, pos in goldBugTaggedNormalized if pos == currentpos] # count only current pos\n", " freqs = nltk.FreqDist(words).most_common(20) # take a subset of most common words\n", " plt.subplot(goldBugTagsGridRows, 3, (idx+1)) # select the grid location that corresponds to the index (of 14)\n", " plt.plot([count for token, count in freqs]) # plot the counts\n", " plt.xticks(range(len(freqs)), [token for token, count in freqs], rotation=45) # plot the words\n", " plt.title(currentpos) # set the title" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Comparing Parts of Speech across Texts" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at linguistic phenomenon within a text can be enlightening, as we've seen, but sometimes it's also useful to compare what we observe with other texts. For instance, what can we say about the ratio of adjectives in one text until we compare it with another?\n", "\n", "We've been focusing on _The Gold Bug_ (in part because acquring a text from a URL is such a useful operation), but our NLTK data also includes several corpora already available locally. For instance, there's a set of texts from Gutenberg that are available – we can view the list of file names with ```nltk.corpus.gutenberg.fileids()```.\n", "\n", "We can also view the text length of each one (note that we're using a [format specification](https://docs.python.org/3.4/library/string.html#formatspec) in order to separate our thousands)." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "austen-emma.txt: 887,071\n", "austen-persuasion.txt: 466,292\n", "austen-sense.txt: 673,022\n", "bible-kjv.txt: 4,332,554\n", "blake-poems.txt: 38,153\n", "bryant-stories.txt: 249,439\n", "burgess-busterbrown.txt: 84,663\n", "carroll-alice.txt: 144,395\n", "chesterton-ball.txt: 457,450\n", "chesterton-brown.txt: 406,629\n", "chesterton-thursday.txt: 320,525\n", "edgeworth-parents.txt: 935,158\n", "melville-moby_dick.txt: 1,242,990\n", "milton-paradise.txt: 468,220\n", "shakespeare-caesar.txt: 112,310\n", "shakespeare-hamlet.txt: 162,881\n", "shakespeare-macbeth.txt: 100,351\n", "whitman-leaves.txt: 711,215\n" ] } ], "source": [ "for fileid in nltk.corpus.gutenberg.fileids():\n", " text = nltk.corpus.gutenberg.raw(fileid) # raw() reads in the string\n", " length = len(text)\n", " print(fileid + \":\", '{:,}'.format(length))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, care to guess which of Carroll's _Alice in Wonderland_ or Edgar Allan Poe's _The Gold Bug_ seems to have more adjectives compared to the total number of word tokens? Let's define our own helper function. " ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def get_percentage_pos(string, pos):\n", " tokens = nltk.word_tokenize(string)\n", " tagged = nltk.pos_tag(tokens)\n", " matching_tagged = [word for word, p in tagged if pos == p]\n", " return len(matching_tagged) / len(tagged)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now use our function for each one of our texts." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Alice has 4.36% adjectives\n", "Gold Bug has 5.66% adjectives\n" ] } ], "source": [ "aliceString = nltk.corpus.gutenberg.raw(\"carroll-alice.txt\")\n", "print(\"Alice has\", '{:.2%}'.format(get_percentage_pos(aliceString, \"JJ\")), \"adjectives\")\n", "print(\"Gold Bug has\", '{:.2%}'.format(get_percentage_pos(goldBugString, \"JJ\")), \"adjectives\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "According to this, it would appear that _Alice in Wonderland_ has relatively more adjectives than _The Gold Bug_." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Next Steps" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here are some tasks to try:\n", "\n", "* Instead of using a normalized 2-letter code for the verb tags, keep the original tags and try to construct an argument about the different types of verbs in _The Gold Bug_.\n", "* Which part-of-speech has the greatest percentage difference between _Alice_ and _Gold Bug_? Try using a loop for the parts-of-speech.\n", "* Which text in Gutenberg has the greatest percentage of adjectives? Try using a loop for the texts.\n", "\n", "Next we'll look at analyzing [repeating phrases](RepeatingPhrases.ipynb)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "[CC BY-SA](https://creativecommons.org/licenses/by-sa/4.0/) From [The Art of Literary Text Analysis](ArtOfLiteraryTextAnalysis.ipynb) by [Stéfan Sinclair](http://stefansinclair.name) & [Geoffrey Rockwell](http://geoffreyrockwell.com). Edited and revised by [Melissa Mony](http://melissamony.com).
Created February 16, 2015 and last modified December 9, 2015 (Jupyter 4)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 1 }