{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import sys\n", "sys.path.append(\"..\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Now you can get extra information for the profiler if you activate pass verbose= True to optimus" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\argenisleon\\Anaconda3\\lib\\site-packages\\socks.py:58: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working\n", " from collections import Callable\n", "\n", " You are using PySparkling of version 2.4.10, but your PySpark is of\n", " version 2.3.1. Please make sure Spark and PySparkling versions are compatible. \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "f657036e-90b5-4391-8d48-fb3f16f6b8ae\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:Operative System:Windows\n", "INFO:optimus:Just check that Spark and all necessary environments vars are present...\n", "INFO:optimus:-----\n", "INFO:optimus:SPARK_HOME=C:\\opt\\spark\\spark-2.3.1-bin-hadoop2.7\n", "INFO:optimus:HADOOP_HOME=C:\\opt\\hadoop-2.7.7\n", "INFO:optimus:PYSPARK_PYTHON=C:\\Users\\argenisleon\\Anaconda3\\python.exe\n", "INFO:optimus:PYSPARK_DRIVER_PYTHON=jupyter\n", "INFO:optimus:PYSPARK_SUBMIT_ARGS=--jars \"file:///C:/Users/argenisleon/Documents/Optimus/optimus/jars/RedshiftJDBC42-1.2.16.1027.jar,file:///C:/Users/argenisleon/Documents/Optimus/optimus/jars/mysql-connector-java-8.0.16.jar,file:///C:/Users/argenisleon/Documents/Optimus/optimus/jars/ojdbc8.jar,file:///C:/Users/argenisleon/Documents/Optimus/optimus/jars/postgresql-42.2.5.jar\" --driver-class-path \"C:/Users/argenisleon/Documents/Optimus/optimus/jars/RedshiftJDBC42-1.2.16.1027.jar;C:/Users/argenisleon/Documents/Optimus/optimus/jars/mysql-connector-java-8.0.16.jar;C:/Users/argenisleon/Documents/Optimus/optimus/jars/ojdbc8.jar;C:/Users/argenisleon/Documents/Optimus/optimus/jars/postgresql-42.2.5.jar\" --conf \"spark.sql.catalogImplementation=hive\" pyspark-shell\n", "INFO:optimus:JAVA_HOME=C:\\java\n", "INFO:optimus:Pyarrow Installed\n", "INFO:optimus:-----\n", "INFO:optimus:Starting or getting SparkSession and SparkContext...\n", "INFO:optimus:Spark Version:2.3.1\n", "INFO:optimus:Setting checkpoint folder local. If you are in a cluster initialize Optimus with master='your_ip' as param\n", "INFO:optimus:Deleting previous folder if exists...\n", "INFO:optimus:Creating the checkpoint directory...\n", "INFO:optimus:\n", " ____ __ _ \n", " / __ \\____ / /_(_)___ ___ __ _______\n", " / / / / __ \\/ __/ / __ `__ \\/ / / / ___/\n", " / /_/ / /_/ / /_/ / / / / / / /_/ (__ ) \n", " \\____/ .___/\\__/_/_/ /_/ /_/\\__,_/____/ \n", " /_/ \n", " \n", "INFO:optimus:Transform and Roll out...\n", "INFO:optimus:Optimus successfully imported. Have fun :).\n", "INFO:optimus:Config.ini not found\n" ] }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create optimus\n", "from optimus import Optimus\n", "op = Optimus(master=\"local[*]\", app_name = \"optimus\" , checkpoint= True, verbose=True)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "df = op.load.csv(\"data/Meteorite_Landings.csv\").h_repartition()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \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
\n", "
1 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
id
\n", "
2 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
nametype
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
recclass
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
mass (g)
\n", "
5 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
fall
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
year
\n", "
7 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclat
\n", "
8 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclong
\n", "
9 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
GeoLocation
\n", "
10 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
Acfer⋅232\n", "
\n", " 		\n", "
240\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
725.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
27.73944\n", "
\n", " 		\n", "
4.32833\n", "
\n", " 		\n", "
(27.739440,⋅4.328330)\n", "
\n", "
\n", "
Elephant⋅Moraine⋅90232\n", "
\n", " 		\n", "
8641\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L6\n", "
\n", " 		\n", "
16.9\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1990⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-76.28795\n", "
\n", " 		\n", "
156.46841\n", "
\n", " 		\n", "
(-76.287950,⋅156.468410)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020090\n", "
\n", " 		\n", "
30681\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
Martian⋅(shergottite)\n", "
\n", " 		\n", "
7.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.99944\n", "
\n", " 		\n", "
75.26111\n", "
\n", " 		\n", "
(-72.999440,⋅75.261110)\n", "
\n", "
\n", "
Northwest⋅Africa⋅891\n", "
\n", " 		\n", "
31912\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H4\n", "
\n", " 		\n", "
70.8\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2001⋅12:00:00⋅AM\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅93098\n", "
\n", " 		\n", "
19187\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
1.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1993⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.5757\n", "
\n", " 		\n", "
162.56524\n", "
\n", " 		\n", "
(-84.575700,⋅162.565240)\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅94691\n", "
\n", " 		\n", "
20322\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
9.6\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1994⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.0\n", "
\n", " 		\n", "
168.0\n", "
\n", " 		\n", "
(-84.000000,⋅168.000000)\n", "
\n", "
\n", "
Meteorite⋅Hills⋅00977\n", "
\n", " 		\n", "
16211\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
13.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2000⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-79.68333\n", "
\n", " 		\n", "
159.75\n", "
\n", " 		\n", "
(-79.683330,⋅159.750000)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020114\n", "
\n", " 		\n", "
46531\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L3\n", "
\n", " 		\n", "
1.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.98194\n", "
\n", " 		\n", "
75.25167\n", "
\n", " 		\n", "
(-72.981940,⋅75.251670)\n", "
\n", "
\n", "
Pecora⋅Escarpment⋅91483\n", "
\n", " 		\n", "
18774\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
5.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-85.55819\n", "
\n", " 		\n", "
-68.31586\n", "
\n", " 		\n", "
(-85.558190,⋅-68.315860)\n", "
\n", "
\n", "
Ramlat⋅as⋅Sahmah⋅390\n", "
\n", " 		\n", "
55656\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H3.8-6\n", "
\n", " 		\n", "
0.69\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2010⋅12:00:00⋅AM\n", "
\n", " 		\n", "
20.0949\n", "
\n", " 		\n", "
55.69318\n", "
\n", " 		\n", "
(20.094900,⋅55.693180)\n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df.table(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Profiler dump mode (Faster). It just handle the column data type as present in the dataframe" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'name': 'string', 'id': 'int', 'nametype': 'string', 'recclass': 'string', 'mass (g)': 'double', 'fall': 'string', 'year': 'string', 'reclat': 'double', 'reclong': 'double', 'GeoLocation': 'string'}\n", "Including 'nan' as Null in processing 'name'\n", "Including 'nan' as Null in processing 'name'\n", "Including 'nan' as Null in processing 'nametype'\n", "Including 'nan' as Null in processing 'recclass'\n", "Including 'nan' as Null in processing 'fall'\n", "Including 'nan' as Null in processing 'year'\n", "Including 'nan' as Null in processing 'GeoLocation'\n" ] }, { "data": { "text/html": [ "\n", "
\n", "

Overview

\n", "
\n", "
\n", "
\n", "

Dataset info

\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "
Number of columns10
Number of rows45716
Total Missing (%)0.49%
Total size in memory64.0 MB
\n", "
\n", "
\n", "

Column 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", "
String1
Numeric0
Date0
Bool0
Array0
Not available0
\n", "
\n", "
\n", "\n", "\n", "
\n", "
\n", "\n", " \n", "\n", "
\n", "
\n", "

name

\n", " categorical\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unique
Unique (%) 99.56
Missing0.0
Missing (%)0
\n", "
\n", "

\n", " Datatypes\n", "

\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "
\n", " String\n", " \n", " 45716\n", "
\n", " Integer\n", " \n", " 0\n", "
\n", " Float\n", " \n", " 0\n", "
\n", " Bool\n", " \n", " 0\n", "
\n", " Date\n", " \n", " 0\n", "
\n", " Missing\n", " \n", " 0\n", "
\n", " Null\n", " \n", " 0\n", "
\n", " \n", "\n", "
\n", "
\n", "

Frequency

\n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
ValueCountFrequency (%)
Święcany10.002%
Łowicz10.002%
Österplana 06410.002%
Österplana 06310.002%
Österplana 06210.002%
Österplana 06110.002%
Österplana 06010.002%
Österplana 05910.002%
Österplana 05810.002%
Österplana 05710.002%
\"Missing\"00.0%
\n", "
\n", " \n", "\n", " \n", "
\n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
\n", "\n", "
\n", " \n", "
\n", "
\n", "
\n", " \n", "
\n", "\n", "
\n", "
\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \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
\n", "
1 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
id
\n", "
2 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
nametype
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
recclass
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
mass (g)
\n", "
5 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
fall
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
year
\n", "
7 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclat
\n", "
8 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclong
\n", "
9 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
GeoLocation
\n", "
10 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
Acfer⋅232\n", "
\n", " 		\n", "
240\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
725.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
27.73944\n", "
\n", " 		\n", "
4.32833\n", "
\n", " 		\n", "
(27.739440,⋅4.328330)\n", "
\n", "
\n", "
Elephant⋅Moraine⋅90232\n", "
\n", " 		\n", "
8641\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L6\n", "
\n", " 		\n", "
16.9\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1990⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-76.28795\n", "
\n", " 		\n", "
156.46841\n", "
\n", " 		\n", "
(-76.287950,⋅156.468410)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020090\n", "
\n", " 		\n", "
30681\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
Martian⋅(shergottite)\n", "
\n", " 		\n", "
7.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.99944\n", "
\n", " 		\n", "
75.26111\n", "
\n", " 		\n", "
(-72.999440,⋅75.261110)\n", "
\n", "
\n", "
Northwest⋅Africa⋅891\n", "
\n", " 		\n", "
31912\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H4\n", "
\n", " 		\n", "
70.8\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2001⋅12:00:00⋅AM\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅93098\n", "
\n", " 		\n", "
19187\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
1.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1993⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.5757\n", "
\n", " 		\n", "
162.56524\n", "
\n", " 		\n", "
(-84.575700,⋅162.565240)\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅94691\n", "
\n", " 		\n", "
20322\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
9.6\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1994⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.0\n", "
\n", " 		\n", "
168.0\n", "
\n", " 		\n", "
(-84.000000,⋅168.000000)\n", "
\n", "
\n", "
Meteorite⋅Hills⋅00977\n", "
\n", " 		\n", "
16211\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
13.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2000⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-79.68333\n", "
\n", " 		\n", "
159.75\n", "
\n", " 		\n", "
(-79.683330,⋅159.750000)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020114\n", "
\n", " 		\n", "
46531\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L3\n", "
\n", " 		\n", "
1.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.98194\n", "
\n", " 		\n", "
75.25167\n", "
\n", " 		\n", "
(-72.981940,⋅75.251670)\n", "
\n", "
\n", "
Pecora⋅Escarpment⋅91483\n", "
\n", " 		\n", "
18774\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
5.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-85.55819\n", "
\n", " 		\n", "
-68.31586\n", "
\n", " 		\n", "
(-85.558190,⋅-68.315860)\n", "
\n", "
\n", "
Ramlat⋅as⋅Sahmah⋅390\n", "
\n", " 		\n", "
55656\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H3.8-6\n", "
\n", " 		\n", "
0.69\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2010⋅12:00:00⋅AM\n", "
\n", " 		\n", "
20.0949\n", "
\n", " 		\n", "
55.69318\n", "
\n", " 		\n", "
(20.094900,⋅55.693180)\n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "op.profiler.run(df, \"name\", infer=False, approx_count= True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Profiler smart mode (Slower). It just try to infer the column data type and present extra data accordingly. From example datetype columns get extra histograms about minutes, day, week and month. Also can detect array types on data." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:Processing column 'GeoLocation'...\n", "INFO:optimus:_count_data_types() executed in 36.83 sec\n", "INFO:optimus:count_data_types() executed in 36.84 sec\n", "INFO:optimus:cast_columns() executed in 0.0 sec\n", "INFO:optimus:agg_exprs() executed in 4.67 sec\n", "INFO:optimus:general_stats() executed in 4.68 sec\n", "INFO:optimus:------------------------------\n", "INFO:optimus:Processing column 'GeoLocation'...\n", "INFO:optimus:frequency() executed in 6.22 sec\n", "INFO:optimus:stats_by_column() executed in 0.0 sec\n", "INFO:optimus:Using 'column_exp' to process column 'GeoLocation_len' with function func_col_exp\n", "INFO:optimus:Using 'column_exp' to process column 'GeoLocation_len' with function _bucketizer\n", "INFO:optimus:hist() executed in 4.79 sec\n", "INFO:optimus:hist_string() executed in 8.07 sec\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Including 'nan' as Null in processing 'name'\n", "Including 'nan' as Null in processing 'nametype'\n", "Including 'nan' as Null in processing 'recclass'\n", "Including 'nan' as Null in processing 'fall'\n", "Including 'nan' as Null in processing 'year'\n", "Including 'nan' as Null in processing 'GeoLocation'\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:dataset_info() executed in 3.87 sec\n" ] }, { "data": { "text/html": [ "\n", "
\n", "

Overview

\n", "
\n", "
\n", "
\n", "

Dataset info

\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "
Number of columns10
Number of rows45716
Total Missing (%)0.49%
Total size in memory80.0 MB
\n", "
\n", "
\n", "

Column 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", "
String0
Numeric0
Date0
Bool0
Array1
Not available0
\n", "
\n", "
\n", "\n", "\n", "
\n", "
\n", "\n", " \n", "\n", "
\n", "
\n", "

GeoLocation

\n", " array\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unique
Unique (%) 36.499
Missing0.0
Missing (%)0
\n", "
\n", "

\n", " Datatypes\n", "

\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "
\n", " String\n", " \n", " 0\n", "
\n", " Integer\n", " \n", " 0\n", "
\n", " Float\n", " \n", " 0\n", "
\n", " Bool\n", " \n", " 0\n", "
\n", " Date\n", " \n", " 0\n", "
\n", " Missing\n", " \n", " 0\n", "
\n", " Null\n", " \n", " 7315\n", "
\n", " \n", "\n", "
\n", "
\n", "

Frequency

\n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
ValueCountFrequency (%)
None731516.001%
(0.000000, 0.000000)621413.593%
(-71.500000, 35.666670)476110.414%
(-84.000000, 168.000000)30406.65%
(-72.000000, 26.000000)15053.292%
(-79.683330, 159.750000)6571.437%
(-76.716670, 159.666670)6371.393%
(-76.183330, 157.166670)5391.179%
(-79.683330, 155.750000)4731.035%
(-84.216670, 160.500000)2630.575%
\"Missing\"00.0%
\n", "
\n", " \n", "\n", " \n", "
\n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
\n", "\n", "
\n", " \n", "
\n", "
\n", "
\n", " \n", "
\n", "\n", "
\n", "
\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \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
\n", "
1 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
id
\n", "
2 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
nametype
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
recclass
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
mass (g)
\n", "
5 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
fall
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
year
\n", "
7 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclat
\n", "
8 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclong
\n", "
9 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
GeoLocation
\n", "
10 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
Acfer⋅232\n", "
\n", " 		\n", "
240\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
725.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
27.73944\n", "
\n", " 		\n", "
4.32833\n", "
\n", " 		\n", "
(27.739440,⋅4.328330)\n", "
\n", "
\n", "
Elephant⋅Moraine⋅90232\n", "
\n", " 		\n", "
8641\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L6\n", "
\n", " 		\n", "
16.9\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1990⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-76.28795\n", "
\n", " 		\n", "
156.46841\n", "
\n", " 		\n", "
(-76.287950,⋅156.468410)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020090\n", "
\n", " 		\n", "
30681\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
Martian⋅(shergottite)\n", "
\n", " 		\n", "
7.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.99944\n", "
\n", " 		\n", "
75.26111\n", "
\n", " 		\n", "
(-72.999440,⋅75.261110)\n", "
\n", "
\n", "
Northwest⋅Africa⋅891\n", "
\n", " 		\n", "
31912\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H4\n", "
\n", " 		\n", "
70.8\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2001⋅12:00:00⋅AM\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅93098\n", "
\n", " 		\n", "
19187\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
1.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1993⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.5757\n", "
\n", " 		\n", "
162.56524\n", "
\n", " 		\n", "
(-84.575700,⋅162.565240)\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅94691\n", "
\n", " 		\n", "
20322\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
9.6\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1994⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.0\n", "
\n", " 		\n", "
168.0\n", "
\n", " 		\n", "
(-84.000000,⋅168.000000)\n", "
\n", "
\n", "
Meteorite⋅Hills⋅00977\n", "
\n", " 		\n", "
16211\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
13.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2000⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-79.68333\n", "
\n", " 		\n", "
159.75\n", "
\n", " 		\n", "
(-79.683330,⋅159.750000)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020114\n", "
\n", " 		\n", "
46531\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L3\n", "
\n", " 		\n", "
1.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.98194\n", "
\n", " 		\n", "
75.25167\n", "
\n", " 		\n", "
(-72.981940,⋅75.251670)\n", "
\n", "
\n", "
Pecora⋅Escarpment⋅91483\n", "
\n", " 		\n", "
18774\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
5.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-85.55819\n", "
\n", " 		\n", "
-68.31586\n", "
\n", " 		\n", "
(-85.558190,⋅-68.315860)\n", "
\n", "
\n", "
Ramlat⋅as⋅Sahmah⋅390\n", "
\n", " 		\n", "
55656\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H3.8-6\n", "
\n", " 		\n", "
0.69\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2010⋅12:00:00⋅AM\n", "
\n", " 		\n", "
20.0949\n", "
\n", " 		\n", "
55.69318\n", "
\n", " 		\n", "
(20.094900,⋅55.693180)\n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:optimus:run() executed in 65.79 sec\n" ] } ], "source": [ "op.profiler.run(df, \"GeoLocation\",infer=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot profile for a specific column" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Including 'nan' as Null in processing 'name'\n", "Including 'nan' as Null in processing 'nametype'\n", "Including 'nan' as Null in processing 'recclass'\n", "Including 'nan' as Null in processing 'fall'\n", "Including 'nan' as Null in processing 'year'\n", "Including 'nan' as Null in processing 'GeoLocation'\n" ] }, { "data": { "text/html": [ "\n", "
\n", "

Overview

\n", "
\n", "
\n", "
\n", "

Dataset info

\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "
Number of columns10
Number of rows45716
Total Missing (%)0.49%
Total size in memory100.4 MB
\n", "
\n", "
\n", "

Column 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", "
String0
Numeric1
Date0
Bool0
Array0
Not available0
\n", "
\n", "
\n", "\n", "\n", "
\n", "
\n", "\n", " \n", "\n", "
\n", "
\n", "

reclat

\n", " numeric\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Unique
Unique (%) 28.806
Missing0.0
Missing (%)0
\n", "
\n", "

\n", " Datatypes\n", "

\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "
\n", " String\n", " \n", " 0\n", "
\n", " Integer\n", " \n", " 0\n", "
\n", " Float\n", " \n", " 0\n", "
\n", " Bool\n", " \n", " 0\n", "
\n", " Date\n", " \n", " 0\n", "
\n", " Missing\n", " \n", " 0\n", "
\n", " Null\n", " \n", " 7315\n", "
\n", " \n", "
\n", "

\n", " Basic Stats\n", "

\n", "\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
Mean-39.12258
Minimum-87.36667
Maximum81.16667
Zeros(%)
\n", " \n", "\n", "
\n", "
\n", "

Frequency

\n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
ValueCountFrequency (%)
None731516.001%
0.0643814.083%
-71.5476110.414%
-84.030406.65%
-72.015063.294%
-79.6833311302.472%
-76.716676801.487%
-76.183335391.179%
-84.216672630.575%
-86.366672260.494%
\"Missing\"00.0%
\n", "
\n", " \n", "\n", " \n", "
\n", "\n", "\n", "

Quantile statistics

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Minimum-87.36667
5-th percentile
Q1
Median
Q3
95-th percentile
Maximum81.16667
Range168.53334
Interquartile range0.0
\n", "
\n", "
\n", "

Descriptive statistics

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Standard deviation46.37851
Coef of variation-1.18547
Kurtosis-1.4768
Mean-39.12258
MAD0.0
Skewness
Sum-1502346.20654
Variance2150.96632
\n", "
\n", " \n", "
\n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
\n", "\n", "
\n", " \n", "
\n", "
\n", "
\n", " \n", "
\n", "\n", "
\n", "
\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \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
\n", "
1 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
id
\n", "
2 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
nametype
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
recclass
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
mass (g)
\n", "
5 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
fall
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
year
\n", "
7 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclat
\n", "
8 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclong
\n", "
9 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
GeoLocation
\n", "
10 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
Acfer⋅232\n", "
\n", " 		\n", "
240\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
725.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
27.73944\n", "
\n", " 		\n", "
4.32833\n", "
\n", " 		\n", "
(27.739440,⋅4.328330)\n", "
\n", "
\n", "
Elephant⋅Moraine⋅90232\n", "
\n", " 		\n", "
8641\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L6\n", "
\n", " 		\n", "
16.9\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1990⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-76.28795\n", "
\n", " 		\n", "
156.46841\n", "
\n", " 		\n", "
(-76.287950,⋅156.468410)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020090\n", "
\n", " 		\n", "
30681\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
Martian⋅(shergottite)\n", "
\n", " 		\n", "
7.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.99944\n", "
\n", " 		\n", "
75.26111\n", "
\n", " 		\n", "
(-72.999440,⋅75.261110)\n", "
\n", "
\n", "
Northwest⋅Africa⋅891\n", "
\n", " 		\n", "
31912\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H4\n", "
\n", " 		\n", "
70.8\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2001⋅12:00:00⋅AM\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅93098\n", "
\n", " 		\n", "
19187\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
1.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1993⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.5757\n", "
\n", " 		\n", "
162.56524\n", "
\n", " 		\n", "
(-84.575700,⋅162.565240)\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅94691\n", "
\n", " 		\n", "
20322\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
9.6\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1994⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.0\n", "
\n", " 		\n", "
168.0\n", "
\n", " 		\n", "
(-84.000000,⋅168.000000)\n", "
\n", "
\n", "
Meteorite⋅Hills⋅00977\n", "
\n", " 		\n", "
16211\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
13.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2000⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-79.68333\n", "
\n", " 		\n", "
159.75\n", "
\n", " 		\n", "
(-79.683330,⋅159.750000)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020114\n", "
\n", " 		\n", "
46531\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L3\n", "
\n", " 		\n", "
1.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.98194\n", "
\n", " 		\n", "
75.25167\n", "
\n", " 		\n", "
(-72.981940,⋅75.251670)\n", "
\n", "
\n", "
Pecora⋅Escarpment⋅91483\n", "
\n", " 		\n", "
18774\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
5.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-85.55819\n", "
\n", " 		\n", "
-68.31586\n", "
\n", " 		\n", "
(-85.558190,⋅-68.315860)\n", "
\n", "
\n", "
Ramlat⋅as⋅Sahmah⋅390\n", "
\n", " 		\n", "
55656\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H3.8-6\n", "
\n", " 		\n", "
0.69\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2010⋅12:00:00⋅AM\n", "
\n", " 		\n", "
20.0949\n", "
\n", " 		\n", "
55.69318\n", "
\n", " 		\n", "
(20.094900,⋅55.693180)\n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "op.profiler.run(df, \"reclat\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Output a json file" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot histagram for multiple columns" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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BTJIkSZI6MZBJkiRJUiczCmRJFiW5LMkNSa5P8uIkhybZnOSm9npIG5skH0yyLcm3krxw6Dzr2vibkqyb6ZeSJEmSpLlgpnfIPgD8z6r6TeC3geuBDcBVVbUCuKptAxwHrGg/64HzAJIcCpwBvAg4CjhjX4iTJEmSpPls5ECW5EnAS4ELAKrqgaraA6wBLmrDLgJObO/XABfXwDXAoiSHA8cCm6tqV1XtBjYDq0ftS5IkSZLmipncIXsGsBP4yyTfSPKRJE8EnlZVdwC016e28UuA7UPH72i1/dUlSZIkaV6bSSBbCLwQOK+qXgD8iF9MT5xMJqnVFPUHnyBZn2RLki07d+58uP1KkiRJ0liZSSDbAeyoqmvb9mUMAtqdbSoi7fWuofHLho5fCtw+Rf1Bqur8qlpZVSsXL148g9YlSZIkqb+RA1lVfR/YnuTZrXQ08F1gE7BvpcR1wOXt/SbglLba4irg7jal8XPAMUkOaYt5HNNqkiRJkjSvLZzh8W8CPpbkIOBm4I0MQt6lSU4FbgNOamOvBI4HtgH3tbFU1a4k7wGua+PeXVW7ZtiXJEmSJI29GQWyqvomsHKSXUdPMraA0/Zzno3Axpn0IkmSJElzzUx/D5kkSZIkaUQGMkmSJEnqxEAmSZIkSZ0YyCRJkiSpEwOZJEmSJHViIJMkSZKkTgxkkiRJktSJgUySJEmSOjGQSZIkSVInBjJJkiRJ6sRAJkmSJEmdGMgkSZIkqRMDmSRJkiR1YiCTJEmSpE4MZJIkSZLUiYFMkiRJkjoxkEmSJElSJwYySZIkSerEQCZJkiRJnRjIJEmSJKkTA5kkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6MZBJkiRJUicGMkmSJEnqZMaBLMmCJN9I8pm2fUSSa5PclOQTSQ5q9ce27W1t//Khc5ze6jcmOXamPUmSJEnSXDAbd8jeDFw/tH02cE5VrQB2A6e2+qnA7qp6FnBOG0eSI4G1wHOB1cC5SRbMQl+SJEmSNNZmFMiSLAVOAD7StgO8HLisDbkIOLG9X9O2afuPbuPXAJdU1f1VdQuwDThqJn1JkiRJ0lww0ztk7wfeBvy8bT8F2FNVe9v2DmBJe78E2A7Q9t/dxv9TfZJjJEmSJGneGjmQJXklcFdVfW24PMnQmmbfVMdM/Mz1SbYk2bJz586H1a8kSZIkjZuZ3CH7XeDVSW4FLmEwVfH9wKIkC9uYpcDt7f0OYBlA2/9kYNdwfZJjfklVnV9VK6tq5eLFi2fQuiRJkiT1N3Igq6rTq2ppVS1nsCjHF6rqtcDVwGvasHXA5e39prZN2/+FqqpWX9tWYTwCWAF8ddS+JEmSJGmuWDj9kIft7cAlSd4LfAO4oNUvAD6aZBuDO2NrAapqa5JLge8Ce4HTqupnj0BfkiRJkjRWZiWQVdUXgS+29zczySqJVfUT4KT9HH8mcOZs9CJJkiRJc8Vs/B4ySZIkSdIIDGSSJEmS1ImBTJIkSZI6MZBJkiRJUicGMkmSJEnqxEAmSZIkSZ0YyCRJkiSpEwOZJEmSJHUyK78YWpI03pZvuKJ3CwDcetYJvVuQJGmseIdMkiRJkjoxkEmSJElSJwYySZIkSerEQCZJkiRJnRjIJEmSJKkTA5kkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6Wdi7AUnSgWv5hit6t8CtZ53QuwVJ0gHMO2SSJEmS1ImBTJIkSZI6MZBJkiRJUicGMkmSJEnqxEAmSZIkSZ0YyCRJkiSpEwOZJEmSJHUyciBLsizJ1UmuT7I1yZtb/dAkm5Pc1F4PafUk+WCSbUm+leSFQ+da18bflGTdzL+WJEmSJI2/mdwh2wv8aVU9B1gFnJbkSGADcFVVrQCuatsAxwEr2s964DwYBDjgDOBFwFHAGftCnCRJkiTNZyMHsqq6o6q+3t7/ELgeWAKsAS5qwy4CTmzv1wAX18A1wKIkhwPHApuraldV7QY2A6tH7UuSJEmS5opZeYYsyXLgBcC1wNOq6g4YhDbgqW3YEmD70GE7Wm1/dUmSJEma12YcyJIcDHwSeEtV3TPV0ElqNUV9ss9an2RLki07d+58+M1KkiRJ0hiZUSBL8hgGYexjVfWpVr6zTUWkvd7V6juAZUOHLwVun6L+IFV1flWtrKqVixcvnknrkiRJktTdTFZZDHABcH1VvW9o1yZg30qJ64DLh+qntNUWVwF3tymNnwOOSXJIW8zjmFaTJEmSpHlt4QyO/V3g9cC3k3yz1d4BnAVcmuRU4DbgpLbvSuB4YBtwH/BGgKraleQ9wHVt3LuratcM+pIkSZKkOWHkQFZVX2by578Ajp5kfAGn7edcG4GNo/YiSZIkSXPRrKyyKEmSJEl6+AxkkiRJktTJTJ4hk+aN5Ruu6N0Ct551Qu8WJEmS9CjzDpkkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6MZBJkiRJUieusqhHnSsaSpIkSQPeIZMkSZKkTgxkkiRJktSJgUySJEmSOjGQSZIkSVInBjJJkiRJ6sRAJkmSJEmdGMgkSZIkqRMDmSRJkiR1YiCTJEmSpE4W9m5AkiRNbfmGK3q3wK1nndC7BUmal7xDJkmSJEmdGMgkSZIkqRMDmSRJkiR14jNk85zPHUiSJEnjyztkkiRJktSJgUySJEmSOnHK4ixyeqAkSZKkh2NsAlmS1cAHgAXAR6rqrM4tSZKkOcT/MSppLhqLQJZkAfBh4F8BO4Drkmyqqu/27UySdKDxL/WSpEfTWAQy4ChgW1XdDJDkEmANYCDTAWsc/1I4Dj2Bf1mVJEnzx7gs6rEE2D60vaPVJEmSJGneSlX17oEkJwHHVtUftO3XA0dV1ZsmjFsPrG+bzwZufFQb1Tg5DPhB7yY0J3ntaFReOxqF141G5bUz9/16VS2ebtC4TFncASwb2l4K3D5xUFWdD5z/aDWl8ZVkS1Wt7N2H5h6vHY3Ka0ej8LrRqLx2DhzjMmXxOmBFkiOSHASsBTZ17kmSJEmSHlFjcYesqvYm+RPgcwyWvd9YVVs7tyVJkiRJj6ixCGQAVXUlcGXvPjRnOHVVo/La0ai8djQKrxuNymvnADEWi3pIkiRJ0oFoXJ4hkyRJkqQDjoFMYy/JSUm2Jvl5kpUT9p2eZFuSG5McO1Rf3Wrbkmx49LvWuPGa0FSSbExyV5LvDNUOTbI5yU3t9ZBWT5IPtmvpW0le2K9z9ZZkWZKrk1zf/lv15lb3+tF+JXlckq8m+bt23byr1Y9Icm27bj7RFrsjyWPb9ra2f3nP/jW7DGSaC74D/BvgS8PFJEcyWJHzucBq4NwkC5IsAD4MHAccCZzcxuoA5TWhh+BCBv8eGbYBuKqqVgBXtW0YXEcr2s964LxHqUeNp73An1bVc4BVwGnt3y9eP5rK/cDLq+q3gecDq5OsAs4GzmnXzW7g1Db+VGB3VT0LOKeN0zxhINPYq6rrq2qyXwK+Brikqu6vqluAbcBR7WdbVd1cVQ8Al7SxOnB5TWhKVfUlYNeE8hrgovb+IuDEofrFNXANsCjJ4Y9Opxo3VXVHVX29vf8hcD2wBK8fTaH987+3bT6m/RTwcuCyVp943ey7ni4Djk6SR6ldPcIMZJrLlgDbh7Z3tNr+6jpweU1oFE+rqjtg8Jdu4Kmt7vWkSbVpZC8ArsXrR9Nos3q+CdwFbAb+HthTVXvbkOFr45+um7b/buApj27HeqSMzbL3OrAl+V/Ar06y651Vdfn+DpukVkz+PxpcTvTAtr9rRRqF15MeJMnBwCeBt1TVPVPcvPD6EQBV9TPg+UkWAX8NPGeyYe3V62YeM5BpLFTVK0Y4bAewbGh7KXB7e7+/ug5MU10r0v7cmeTwqrqjTSm7q9W9nvRLkjyGQRj7WFV9qpW9fvSQVNWeJF9k8AzioiQL212w4Wtj33WzI8lC4Mk8eJq15iinLGou2wSsbSsPHcHgAemvAtcBK9pKRQcxWPhjU8c+1Z/XhEaxCVjX3q8DLh+qn9JWy1sF3L1vapoOPO05nguA66vqfUO7vH60X0kWtztjJHk88AoGzx9eDbymDZt43ey7nl4DfKH8ZcLzhr8YWmMvyb8G/huwGNgDfLOqjm373gn8PoNVrt5SVZ9t9eOB9wMLgI1VdWaP3jU+vCY0lSQfB14GHAbcCZwBfBq4FPg14DbgpKra1f4C/iEGqzLeB7yxqrb06Fv9Jfk94H8D3wZ+3srvYPAcmdePJpXktxgs0rGAwQ2SS6vq3UmewWDhqUOBbwCvq6r7kzwO+CiDZxR3AWur6uY+3Wu2GcgkSZIkqROnLEqSJElSJwYySZIkSerEQCZJkiRJnRjIJEmSJKkTA5kkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6+f/WpH0dHKwjDgAAAABJRU5ErkJggg==\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df.plot.frequency([\"id\", \"reclong\"], 10)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
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\n", "
name
\n", "
1 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
id
\n", "
2 (int)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
nametype
\n", "
3 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
recclass
\n", "
4 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
mass (g)
\n", "
5 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
fall
\n", "
6 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
year
\n", "
7 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclat
\n", "
8 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
reclong
\n", "
9 (double)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", " 		\n", "
GeoLocation
\n", "
10 (string)
\n", "
\n", " \n", " nullable\n", " \n", "
\n", "
\n", "
Acfer⋅232\n", "
\n", " 		\n", "
240\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
725.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
27.73944\n", "
\n", " 		\n", "
4.32833\n", "
\n", " 		\n", "
(27.739440,⋅4.328330)\n", "
\n", "
\n", "
Elephant⋅Moraine⋅90232\n", "
\n", " 		\n", "
8641\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L6\n", "
\n", " 		\n", "
16.9\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1990⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-76.28795\n", "
\n", " 		\n", "
156.46841\n", "
\n", " 		\n", "
(-76.287950,⋅156.468410)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020090\n", "
\n", " 		\n", "
30681\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
Martian⋅(shergottite)\n", "
\n", " 		\n", "
7.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.99944\n", "
\n", " 		\n", "
75.26111\n", "
\n", " 		\n", "
(-72.999440,⋅75.261110)\n", "
\n", "
\n", "
Northwest⋅Africa⋅891\n", "
\n", " 		\n", "
31912\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H4\n", "
\n", " 		\n", "
70.8\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2001⋅12:00:00⋅AM\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", " 		\n", "
None\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅93098\n", "
\n", " 		\n", "
19187\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
1.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1993⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.5757\n", "
\n", " 		\n", "
162.56524\n", "
\n", " 		\n", "
(-84.575700,⋅162.565240)\n", "
\n", "
\n", "
Queen⋅Alexandra⋅Range⋅94691\n", "
\n", " 		\n", "
20322\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H6\n", "
\n", " 		\n", "
9.6\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1994⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-84.0\n", "
\n", " 		\n", "
168.0\n", "
\n", " 		\n", "
(-84.000000,⋅168.000000)\n", "
\n", "
\n", "
Meteorite⋅Hills⋅00977\n", "
\n", " 		\n", "
16211\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
13.2\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2000⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-79.68333\n", "
\n", " 		\n", "
159.75\n", "
\n", " 		\n", "
(-79.683330,⋅159.750000)\n", "
\n", "
\n", "
Grove⋅Mountains⋅020114\n", "
\n", " 		\n", "
46531\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
L3\n", "
\n", " 		\n", "
1.0\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2003⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-72.98194\n", "
\n", " 		\n", "
75.25167\n", "
\n", " 		\n", "
(-72.981940,⋅75.251670)\n", "
\n", "
\n", "
Pecora⋅Escarpment⋅91483\n", "
\n", " 		\n", "
18774\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H5\n", "
\n", " 		\n", "
5.5\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/1991⋅12:00:00⋅AM\n", "
\n", " 		\n", "
-85.55819\n", "
\n", " 		\n", "
-68.31586\n", "
\n", " 		\n", "
(-85.558190,⋅-68.315860)\n", "
\n", "
\n", "
Ramlat⋅as⋅Sahmah⋅390\n", "
\n", " 		\n", "
55656\n", "
\n", " 		\n", "
Valid\n", "
\n", " 		\n", "
H3.8-6\n", "
\n", " 		\n", "
0.69\n", "
\n", " 		\n", "
Found\n", "
\n", " 		\n", "
01/01/2010⋅12:00:00⋅AM\n", "
\n", " 		\n", "
20.0949\n", "
\n", " 		\n", "
55.69318\n", "
\n", " 		\n", "
(20.094900,⋅55.693180)\n", "
\n", "
\n", "\n", "\n", "
Viewing 10 of 45716 rows / 10 columns
\n", "
32 partition(s)
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df.table()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Including 'nan' as Null in processing 'name'\n", "Including 'nan' as Null in processing 'nametype'\n", "Including 'nan' as Null in processing 'recclass'\n", "Including 'nan' as Null in processing 'fall'\n", "Including 'nan' as Null in processing 'year'\n", "Including 'nan' as Null in processing 'GeoLocation'\n" ] }, { "data": { "text/plain": [ "{'name': 0,\n", " 'id': 0,\n", " 'nametype': 0,\n", " 'recclass': 0,\n", " 'mass (g)': 131,\n", " 'fall': 0,\n", " 'year': 288,\n", " 'reclat': 7315,\n", " 'reclong': 7315,\n", " 'GeoLocation': 7315}" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.cols.count_na(\"*\")" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "ename": "IndentationError", "evalue": "unexpected indent (, line 12)", "output_type": "error", "traceback": [ "\u001b[1;36m File \u001b[1;32m\"\"\u001b[1;36m, line \u001b[1;32m12\u001b[0m\n\u001b[1;33m df.cols.dtypes()\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mIndentationError\u001b[0m\u001b[1;31m:\u001b[0m unexpected indent\n" ] } ], "source": [ "a = {'name': 0,\n", " 'id': 0,\n", " 'nametype': 0,\n", " 'recclass': 0,\n", " 'mass (g)': 131,\n", " 'fall': 0,\n", " 'year': 288,\n", " 'reclat': 7315,\n", " 'reclong': 7315,\n", " 'GeoLocation': 7315}\n", "\n", " df.cols.dtypes()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "cols = [\"id\",\"mass (g)\",\"reclat\"]\n", "# We drops nulls because correlation can not handle them\n", "df_not_nulls = df.rows.drop_na(cols)\n", "\n", "df_not_nulls.plot.correlation(cols)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "{'cols': ['id', 'mass (g)', 'reclat'],\n", " 'data': array([[ 1. , -0.01794746, 0.27151272],\n", " [-0.01794746, 1. , 0.02908721],\n", " [ 0.27151272, 0.02908721, 1. ]])}" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_not_nulls.cols.correlation([\"id\",\"mass (g)\", \"reclat\"], output=\"array\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "jupytext": { "formats": "ipynb,py:light" }, "kernel_info": { "name": "python3" }, "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": "3.7.1" }, "nteract": { "version": "0.11.6" } }, "nbformat": 4, "nbformat_minor": 2 }