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added a tags snippet
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‎.ipynb_checkpoints/pandas_expand_cells_containing_lists-checkpoint.ipynb

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{
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"metadata": {
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"name": "",
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"signature": "sha256:f31de46477b2663a07c56bdac9684ccc42094e16ec9c87b5caaea8cf66eaf43d"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Expand Cells Containing Lists Into Their Own Variables In Pandas\n",
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"\n",
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"This snippit was written by [Chris R. Albon](http://www.chrisralbon.com/) and is part of his collection of [well-documented Python snippits](https://github.com/chrisalbon/code_py). All code is written in Python 3 in iPython notebook and offered under the [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/)."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# import pandas\n",
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"import pandas as pd"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 20
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# create a dataset\n",
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"raw_data = {'score': [1,2,3], \n",
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" 'tags': [['apple','pear','guava'],['truck','car','plane'],['cat','dog','mouse']]}\n",
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"df = pd.DataFrame(raw_data, columns = ['score', 'tags'])\n",
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"\n",
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"# view the dataset\n",
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"df"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>score</th>\n",
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" <th>tags</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td> 1</td>\n",
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" <td> [apple, pear, guava]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td> 2</td>\n",
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" <td> [truck, car, plane]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td> 3</td>\n",
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" <td> [cat, dog, mouse]</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 24,
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"text": [
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" score tags\n",
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"0 1 [apple, pear, guava]\n",
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"1 2 [truck, car, plane]\n",
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"2 3 [cat, dog, mouse]"
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]
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}
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],
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"prompt_number": 24
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# expand df.tags into its own dataframe\n",
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"tags = df['tags'].apply(pd.Series)\n",
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"\n",
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"# rename each variable is tags\n",
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"tags = tags.rename(columns = lambda x : 'tag_' + str(x))\n",
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"\n",
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"# view the tags dataframe\n",
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"tags"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>tag_0</th>\n",
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" <th>tag_1</th>\n",
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" <th>tag_2</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td> apple</td>\n",
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" <td> pear</td>\n",
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" <td> guava</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td> truck</td>\n",
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" <td> car</td>\n",
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" <td> plane</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td> cat</td>\n",
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" <td> dog</td>\n",
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" <td> mouse</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 25,
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"text": [
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" tag_0 tag_1 tag_2\n",
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"0 apple pear guava\n",
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"1 truck car plane\n",
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"2 cat dog mouse"
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]
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}
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],
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"prompt_number": 25
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# join the tags dataframe back to the original dataframe\n",
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"pd.concat([df[:], tags[:]], axis=1)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>score</th>\n",
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" <th>tags</th>\n",
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" <th>tag_0</th>\n",
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" <th>tag_1</th>\n",
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" <th>tag_2</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td> 1</td>\n",
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" <td> [apple, pear, guava]</td>\n",
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" <td> apple</td>\n",
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" <td> pear</td>\n",
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" <td> guava</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td> 2</td>\n",
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" <td> [truck, car, plane]</td>\n",
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" <td> truck</td>\n",
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" <td> car</td>\n",
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" <td> plane</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td> 3</td>\n",
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" <td> [cat, dog, mouse]</td>\n",
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" <td> cat</td>\n",
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" <td> dog</td>\n",
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" <td> mouse</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 26,
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"text": [
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" score tags tag_0 tag_1 tag_2\n",
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"0 1 [apple, pear, guava] apple pear guava\n",
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"1 2 [truck, car, plane] truck car plane\n",
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"2 3 [cat, dog, mouse] cat dog mouse"
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]
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}
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],
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"prompt_number": 26
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}
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],
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"metadata": {}
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}
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]
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}

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