{ "metadata": { "name": "", "signature": "sha256:b8e8900e9a22df7e17a8a63c78c9a4bd8ce28af9f6b231896356e4fff31d478e" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Indexing and Selecting Data With Pandas\n", "\n", "- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n", "- **Date:** -\n", "- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n", "- **Note:**\n", "\n", "Short verison:\n", "\n", "- .iloc[**row**,**column**]" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# import the pandas module\n", "import pandas as pd" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "# Create an example dataframe about a fictional army\n", "raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'], \n", " 'company': ['1st', '1st', '2nd', '2nd', '1st', '1st', '2nd', '2nd','1st', '1st', '2nd', '2nd'], \n", " 'deaths': [523, 52, 25, 616, 43, 234, 523, 62, 62, 73, 37, 35], \n", " 'battles': [5, 42, 2, 2, 4, 7, 8, 3, 4, 7, 8, 9], \n", " 'size': [1045, 957, 1099, 1400, 1592, 1006, 987, 849, 973, 1005, 1099, 1523],\n", " 'veterans': [1, 5, 62, 26, 73, 37, 949, 48, 48, 435, 63, 345],\n", " 'readiness': [1, 2, 3, 3, 2, 1, 2, 3, 2, 1, 2, 3],\n", " 'armored': [1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1],\n", " 'deserters': [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],\n", " 'origin': ['Arizona', 'California', 'Texas', 'Florida', 'Maine', 'Iowa', 'Alaska', 'Washington', 'Oregon', 'Wyoming', 'Louisana', 'Georgia']}\n", "\n", "df = pd.DataFrame(raw_data, columns = ['regiment', 'company', 'deaths', 'battles', 'size', 'veterans', 'readiness', 'armored', 'deserters', 'origin'])\n", "\n", "df = df.set_index('origin')\n", "\n", "df.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
California Nighthawks 1st 52 42 957 5 2 0 24
Texas Nighthawks 2nd 25 2 1099 62 3 1 31
Florida Nighthawks 2nd 616 2 1400 26 3 1 2
Maine Dragoons 1st 43 4 1592 73 2 0 3
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "California Nighthawks 1st 52 42 957 5 2 \n", "Texas Nighthawks 2nd 25 2 1099 62 3 \n", "Florida Nighthawks 2nd 616 2 1400 26 3 \n", "Maine Dragoons 1st 43 4 1592 73 2 \n", "\n", " armored deserters \n", "origin \n", "Arizona 1 4 \n", "California 0 24 \n", "Texas 1 31 \n", "Florida 1 2 \n", "Maine 0 3 " ] } ], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select a column" ] }, { "cell_type": "code", "collapsed": false, "input": [ "df['size']" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "origin\n", "Arizona 1045\n", "California 957\n", "Texas 1099\n", "Florida 1400\n", "Maine 1592\n", "Iowa 1006\n", "Alaska 987\n", "Washington 849\n", "Oregon 973\n", "Wyoming 1005\n", "Louisana 1099\n", "Georgia 1523\n", "Name: size, dtype: int64" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select multiple columns" ] }, { "cell_type": "code", "collapsed": false, "input": [ "df[['size', 'veterans']]" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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sizeveterans
origin
Arizona 1045 1
California 957 5
Texas 1099 62
Florida 1400 26
Maine 1592 73
Iowa 1006 37
Alaska 987 949
Washington 849 48
Oregon 973 48
Wyoming 1005 435
Louisana 1099 63
Georgia 1523 345
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ " size veterans\n", "origin \n", "Arizona 1045 1\n", "California 957 5\n", "Texas 1099 62\n", "Florida 1400 26\n", "Maine 1592 73\n", "Iowa 1006 37\n", "Alaska 987 949\n", "Washington 849 48\n", "Oregon 973 48\n", "Wyoming 1005 435\n", "Louisana 1099 63\n", "Georgia 1523 345" ] } ], "prompt_number": 5 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select all rows by index label" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Select all rows with the index label \"Arizona\"\n", "df.loc[:'Arizona']" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "\n", " armored deserters \n", "origin \n", "Arizona 1 4 " ] } ], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select rows by row number" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Select every row up to 3\n", "df.iloc[:2]" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
California Nighthawks 1st 52 42 957 5 2 0 24
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 7, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "California Nighthawks 1st 52 42 957 5 2 \n", "\n", " armored deserters \n", "origin \n", "Arizona 1 4 \n", "California 0 24 " ] } ], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select the second and third row\n", "df.iloc[1:2]" ], "language": "python", "metadata": {}, "outputs": [ { "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", "
regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
California Nighthawks 1st 52 42 957 5 2 0 24
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 8, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "California Nighthawks 1st 52 42 957 5 2 \n", "\n", " armored deserters \n", "origin \n", "California 0 24 " ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select every row after the third row\n", "df.iloc[2:]" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Texas Nighthawks 2nd 25 2 1099 62 3 1 31
Florida Nighthawks 2nd 616 2 1400 26 3 1 2
Maine Dragoons 1st 43 4 1592 73 2 0 3
Iowa Dragoons 1st 234 7 1006 37 1 1 4
Alaska Dragoons 2nd 523 8 987 949 2 0 24
Washington Dragoons 2nd 62 3 849 48 3 1 31
Oregon Scouts 1st 62 4 973 48 2 0 2
Wyoming Scouts 1st 73 7 1005 435 1 0 3
Louisana Scouts 2nd 37 8 1099 63 2 1 2
Georgia Scouts 2nd 35 9 1523 345 3 1 3
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 9, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Texas Nighthawks 2nd 25 2 1099 62 3 \n", "Florida Nighthawks 2nd 616 2 1400 26 3 \n", "Maine Dragoons 1st 43 4 1592 73 2 \n", "Iowa Dragoons 1st 234 7 1006 37 1 \n", "Alaska Dragoons 2nd 523 8 987 949 2 \n", "Washington Dragoons 2nd 62 3 849 48 3 \n", "Oregon Scouts 1st 62 4 973 48 2 \n", "Wyoming Scouts 1st 73 7 1005 435 1 \n", "Louisana Scouts 2nd 37 8 1099 63 2 \n", "Georgia Scouts 2nd 35 9 1523 345 3 \n", "\n", " armored deserters \n", "origin \n", "Texas 1 31 \n", "Florida 1 2 \n", "Maine 0 3 \n", "Iowa 1 4 \n", "Alaska 0 24 \n", "Washington 1 31 \n", "Oregon 0 2 \n", "Wyoming 0 3 \n", "Louisana 1 2 \n", "Georgia 1 3 " ] } ], "prompt_number": 9 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select columns by column position" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Select the first 2 columns\n", "df.iloc[:,:2]" ], "language": "python", "metadata": {}, "outputs": [ { "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", "
regimentcompany
origin
Arizona Nighthawks 1st
California Nighthawks 1st
Texas Nighthawks 2nd
Florida Nighthawks 2nd
Maine Dragoons 1st
Iowa Dragoons 1st
Alaska Dragoons 2nd
Washington Dragoons 2nd
Oregon Scouts 1st
Wyoming Scouts 1st
Louisana Scouts 2nd
Georgia Scouts 2nd
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ " regiment company\n", "origin \n", "Arizona Nighthawks 1st\n", "California Nighthawks 1st\n", "Texas Nighthawks 2nd\n", "Florida Nighthawks 2nd\n", "Maine Dragoons 1st\n", "Iowa Dragoons 1st\n", "Alaska Dragoons 2nd\n", "Washington Dragoons 2nd\n", "Oregon Scouts 1st\n", "Wyoming Scouts 1st\n", "Louisana Scouts 2nd\n", "Georgia Scouts 2nd" ] } ], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select by conditionals (boolean)" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Select rows where df.deaths is greater than 50\n", "df[df['deaths'] > 50]" ], "language": "python", "metadata": {}, "outputs": [ { "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", "
regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
California Nighthawks 1st 52 42 957 5 2 0 24
Florida Nighthawks 2nd 616 2 1400 26 3 1 2
Iowa Dragoons 1st 234 7 1006 37 1 1 4
Alaska Dragoons 2nd 523 8 987 949 2 0 24
Washington Dragoons 2nd 62 3 849 48 3 1 31
Oregon Scouts 1st 62 4 973 48 2 0 2
Wyoming Scouts 1st 73 7 1005 435 1 0 3
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 11, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "California Nighthawks 1st 52 42 957 5 2 \n", "Florida Nighthawks 2nd 616 2 1400 26 3 \n", "Iowa Dragoons 1st 234 7 1006 37 1 \n", "Alaska Dragoons 2nd 523 8 987 949 2 \n", "Washington Dragoons 2nd 62 3 849 48 3 \n", "Oregon Scouts 1st 62 4 973 48 2 \n", "Wyoming Scouts 1st 73 7 1005 435 1 \n", "\n", " armored deserters \n", "origin \n", "Arizona 1 4 \n", "California 0 24 \n", "Florida 1 2 \n", "Iowa 1 4 \n", "Alaska 0 24 \n", "Washington 1 31 \n", "Oregon 0 2 \n", "Wyoming 0 3 " ] } ], "prompt_number": 11 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select rows where df.deaths is greater than 500 or less than 50\n", "df[(df['deaths'] > 500) | (df['deaths'] < 50)]" ], "language": "python", "metadata": {}, "outputs": [ { "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", "
regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
Texas Nighthawks 2nd 25 2 1099 62 3 1 31
Florida Nighthawks 2nd 616 2 1400 26 3 1 2
Maine Dragoons 1st 43 4 1592 73 2 0 3
Alaska Dragoons 2nd 523 8 987 949 2 0 24
Louisana Scouts 2nd 37 8 1099 63 2 1 2
Georgia Scouts 2nd 35 9 1523 345 3 1 3
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 12, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "Texas Nighthawks 2nd 25 2 1099 62 3 \n", "Florida Nighthawks 2nd 616 2 1400 26 3 \n", "Maine Dragoons 1st 43 4 1592 73 2 \n", "Alaska Dragoons 2nd 523 8 987 949 2 \n", "Louisana Scouts 2nd 37 8 1099 63 2 \n", "Georgia Scouts 2nd 35 9 1523 345 3 \n", "\n", " armored deserters \n", "origin \n", "Arizona 1 4 \n", "Texas 1 31 \n", "Florida 1 2 \n", "Maine 0 3 \n", "Alaska 0 24 \n", "Louisana 1 2 \n", "Georgia 1 3 " ] } ], "prompt_number": 12 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select all the regiments not named \"Dragoons\"\n", "df[~(df['regiment'] == 'Dragoons')]" ], "language": "python", "metadata": {}, "outputs": [ { "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", "
regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
origin
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
California Nighthawks 1st 52 42 957 5 2 0 24
Texas Nighthawks 2nd 25 2 1099 62 3 1 31
Florida Nighthawks 2nd 616 2 1400 26 3 1 2
Oregon Scouts 1st 62 4 973 48 2 0 2
Wyoming Scouts 1st 73 7 1005 435 1 0 3
Louisana Scouts 2nd 37 8 1099 63 2 1 2
Georgia Scouts 2nd 35 9 1523 345 3 1 3
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 13, "text": [ " regiment company deaths battles size veterans readiness \\\n", "origin \n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "California Nighthawks 1st 52 42 957 5 2 \n", "Texas Nighthawks 2nd 25 2 1099 62 3 \n", "Florida Nighthawks 2nd 616 2 1400 26 3 \n", "Oregon Scouts 1st 62 4 973 48 2 \n", "Wyoming Scouts 1st 73 7 1005 435 1 \n", "Louisana Scouts 2nd 37 8 1099 63 2 \n", "Georgia Scouts 2nd 35 9 1523 345 3 \n", "\n", " armored deserters \n", "origin \n", "Arizona 1 4 \n", "California 0 24 \n", "Texas 1 31 \n", "Florida 1 2 \n", "Oregon 0 2 \n", "Wyoming 0 3 \n", "Louisana 1 2 \n", "Georgia 1 3 " ] } ], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## .ix\n", "\n", ".ix is the combination of both .loc and .iloc. Integers are first considered labels, but if not found, falls back on positional indexing" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Select the rows called Texas and Arizona\n", "df.ix[['Arizona', 'Texas']]" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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regimentcompanydeathsbattlessizeveteransreadinessarmoreddeserters
Arizona Nighthawks 1st 523 5 1045 1 1 1 4
Texas Nighthawks 2nd 25 2 1099 62 3 1 31
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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 18, "text": [ " regiment company deaths battles size veterans readiness \\\n", "Arizona Nighthawks 1st 523 5 1045 1 1 \n", "Texas Nighthawks 2nd 25 2 1099 62 3 \n", "\n", " armored deserters \n", "Arizona 1 4 \n", "Texas 1 31 " ] } ], "prompt_number": 18 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select the third cell in the row named Arizona\n", "df.ix['Arizona', 'deaths']" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 32, "text": [ "523" ] } ], "prompt_number": 32 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select the third cell in the row named Arizona\n", "df.ix['Arizona', 2]" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 27, "text": [ "523" ] } ], "prompt_number": 27 }, { "cell_type": "code", "collapsed": false, "input": [ "# Select the third cell down in the column named deaths\n", "df.ix[2, 'deaths']" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 30, "text": [ "25" ] } ], "prompt_number": 30 }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [] } ], "metadata": {} } ] }