1493 lines
38 KiB
Plaintext
1493 lines
38 KiB
Plaintext
{
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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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"___\n",
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"\n",
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"<a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>\n",
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"___"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": true
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},
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"source": [
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"# Merging, Joining, and Concatenating\n",
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"\n",
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"There are 3 main ways of combining DataFrames together: Merging, Joining and Concatenating. In this lecture we will discuss these 3 methods with examples.\n",
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"\n",
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"____"
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]
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},
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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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"### Example DataFrames"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],\n",
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" 'B': ['B0', 'B1', 'B2', 'B3'],\n",
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" 'C': ['C0', 'C1', 'C2', 'C3'],\n",
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" 'D': ['D0', 'D1', 'D2', 'D3']},\n",
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" index=[0, 1, 2, 3])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],\n",
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" 'B': ['B4', 'B5', 'B6', 'B7'],\n",
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" 'C': ['C4', 'C5', 'C6', 'C7'],\n",
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" 'D': ['D4', 'D5', 'D6', 'D7']},\n",
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" index=[4, 5, 6, 7]) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],\n",
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" 'B': ['B8', 'B9', 'B10', 'B11'],\n",
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" 'C': ['C8', 'C9', 'C10', 'C11'],\n",
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" 'D': ['D8', 'D9', 'D10', 'D11']},\n",
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" index=[8, 9, 10, 11])"
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]
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},
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{
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" <th>3</th>\n",
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" A B C D\n",
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"source": [
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"## Concatenation\n",
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"\n",
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"Concatenation basically glues together DataFrames. Keep in mind that dimensions should match along the axis you are concatenating on. You can use **pd.concat** and pass in a list of DataFrames to concatenate together:"
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]
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" <th>7</th>\n",
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" <th>11</th>\n",
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" <td>D2</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>A3</td>\n",
|
|
" <td>B3</td>\n",
|
|
" <td>C3</td>\n",
|
|
" <td>D3</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A4</td>\n",
|
|
" <td>B4</td>\n",
|
|
" <td>C4</td>\n",
|
|
" <td>D4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A5</td>\n",
|
|
" <td>B5</td>\n",
|
|
" <td>C5</td>\n",
|
|
" <td>D5</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A6</td>\n",
|
|
" <td>B6</td>\n",
|
|
" <td>C6</td>\n",
|
|
" <td>D6</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A7</td>\n",
|
|
" <td>B7</td>\n",
|
|
" <td>C7</td>\n",
|
|
" <td>D7</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A8</td>\n",
|
|
" <td>B8</td>\n",
|
|
" <td>C8</td>\n",
|
|
" <td>D8</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A9</td>\n",
|
|
" <td>B9</td>\n",
|
|
" <td>C9</td>\n",
|
|
" <td>D9</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A10</td>\n",
|
|
" <td>B10</td>\n",
|
|
" <td>C10</td>\n",
|
|
" <td>D10</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>A11</td>\n",
|
|
" <td>B11</td>\n",
|
|
" <td>C11</td>\n",
|
|
" <td>D11</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" A B C D A B C D A B C D\n",
|
|
"0 A0 B0 C0 D0 NaN NaN NaN NaN NaN NaN NaN NaN\n",
|
|
"1 A1 B1 C1 D1 NaN NaN NaN NaN NaN NaN NaN NaN\n",
|
|
"2 A2 B2 C2 D2 NaN NaN NaN NaN NaN NaN NaN NaN\n",
|
|
"3 A3 B3 C3 D3 NaN NaN NaN NaN NaN NaN NaN NaN\n",
|
|
"4 NaN NaN NaN NaN A4 B4 C4 D4 NaN NaN NaN NaN\n",
|
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"5 NaN NaN NaN NaN A5 B5 C5 D5 NaN NaN NaN NaN\n",
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"6 NaN NaN NaN NaN A6 B6 C6 D6 NaN NaN NaN NaN\n",
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"7 NaN NaN NaN NaN A7 B7 C7 D7 NaN NaN NaN NaN\n",
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"8 NaN NaN NaN NaN NaN NaN NaN NaN A8 B8 C8 D8\n",
|
|
"9 NaN NaN NaN NaN NaN NaN NaN NaN A9 B9 C9 D9\n",
|
|
"10 NaN NaN NaN NaN NaN NaN NaN NaN A10 B10 C10 D10\n",
|
|
"11 NaN NaN NaN NaN NaN NaN NaN NaN A11 B11 C11 D11"
|
|
]
|
|
},
|
|
"execution_count": 18,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"pd.concat([df1,df2,df3],axis=1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"_____\n",
|
|
"## Example DataFrames"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"left = pd.DataFrame({'key': ['K0', 'K1', 'K2', 'K3'],\n",
|
|
" 'A': ['A0', 'A1', 'A2', 'A3'],\n",
|
|
" 'B': ['B0', 'B1', 'B2', 'B3']})\n",
|
|
" \n",
|
|
"right = pd.DataFrame({'key': ['K0', 'K1', 'K2', 'K3'],\n",
|
|
" 'C': ['C0', 'C1', 'C2', 'C3'],\n",
|
|
" 'D': ['D0', 'D1', 'D2', 'D3']}) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {
|
|
"collapsed": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>A</th>\n",
|
|
" <th>B</th>\n",
|
|
" <th>key</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
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" <tbody>\n",
|
|
" <tr>\n",
|
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" <th>0</th>\n",
|
|
" <td>A0</td>\n",
|
|
" <td>B0</td>\n",
|
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" <td>K0</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>1</th>\n",
|
|
" <td>A1</td>\n",
|
|
" <td>B1</td>\n",
|
|
" <td>K1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>A2</td>\n",
|
|
" <td>B2</td>\n",
|
|
" <td>K2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>A3</td>\n",
|
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" <td>B3</td>\n",
|
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" <td>K3</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
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],
|
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"text/plain": [
|
|
" A B key\n",
|
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"0 A0 B0 K0\n",
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"1 A1 B1 K1\n",
|
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"2 A2 B2 K2\n",
|
|
"3 A3 B3 K3"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"left"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"metadata": {
|
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"collapsed": false
|
|
},
|
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"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
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" <thead>\n",
|
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" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
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" <th>C</th>\n",
|
|
" <th>D</th>\n",
|
|
" <th>key</th>\n",
|
|
" </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",
|
|
" <td>C0</td>\n",
|
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" <td>D0</td>\n",
|
|
" <td>K0</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>1</th>\n",
|
|
" <td>C1</td>\n",
|
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" <td>D1</td>\n",
|
|
" <td>K1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
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" <th>2</th>\n",
|
|
" <td>C2</td>\n",
|
|
" <td>D2</td>\n",
|
|
" <td>K2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>C3</td>\n",
|
|
" <td>D3</td>\n",
|
|
" <td>K3</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
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],
|
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"text/plain": [
|
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" C D key\n",
|
|
"0 C0 D0 K0\n",
|
|
"1 C1 D1 K1\n",
|
|
"2 C2 D2 K2\n",
|
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"3 C3 D3 K3"
|
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]
|
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},
|
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"execution_count": 30,
|
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"metadata": {},
|
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"output_type": "execute_result"
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}
|
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],
|
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"source": [
|
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"right"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"___"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Merging\n",
|
|
"\n",
|
|
"The **merge** function allows you to merge DataFrames together using a similar logic as merging SQL Tables together. For example:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
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"metadata": {
|
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"collapsed": false
|
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},
|
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"outputs": [
|
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{
|
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"data": {
|
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"text/html": [
|
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"<div>\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",
|
|
" <th></th>\n",
|
|
" <th>A</th>\n",
|
|
" <th>B</th>\n",
|
|
" <th>key</th>\n",
|
|
" <th>C</th>\n",
|
|
" <th>D</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>A0</td>\n",
|
|
" <td>B0</td>\n",
|
|
" <td>K0</td>\n",
|
|
" <td>C0</td>\n",
|
|
" <td>D0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>A1</td>\n",
|
|
" <td>B1</td>\n",
|
|
" <td>K1</td>\n",
|
|
" <td>C1</td>\n",
|
|
" <td>D1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>A2</td>\n",
|
|
" <td>B2</td>\n",
|
|
" <td>K2</td>\n",
|
|
" <td>C2</td>\n",
|
|
" <td>D2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>A3</td>\n",
|
|
" <td>B3</td>\n",
|
|
" <td>K3</td>\n",
|
|
" <td>C3</td>\n",
|
|
" <td>D3</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
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"text/plain": [
|
|
" A B key C D\n",
|
|
"0 A0 B0 K0 C0 D0\n",
|
|
"1 A1 B1 K1 C1 D1\n",
|
|
"2 A2 B2 K2 C2 D2\n",
|
|
"3 A3 B3 K3 C3 D3"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"pd.merge(left,right,how='inner',on='key')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Or to show a more complicated example:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"left = pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],\n",
|
|
" 'key2': ['K0', 'K1', 'K0', 'K1'],\n",
|
|
" 'A': ['A0', 'A1', 'A2', 'A3'],\n",
|
|
" 'B': ['B0', 'B1', 'B2', 'B3']})\n",
|
|
" \n",
|
|
"right = pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],\n",
|
|
" 'key2': ['K0', 'K0', 'K0', 'K0'],\n",
|
|
" 'C': ['C0', 'C1', 'C2', 'C3'],\n",
|
|
" 'D': ['D0', 'D1', 'D2', 'D3']})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"metadata": {
|
|
"collapsed": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>A</th>\n",
|
|
" <th>B</th>\n",
|
|
" <th>key1</th>\n",
|
|
" <th>key2</th>\n",
|
|
" <th>C</th>\n",
|
|
" <th>D</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
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" <tbody>\n",
|
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" <tr>\n",
|
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" <th>0</th>\n",
|
|
" <td>A0</td>\n",
|
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" <td>B0</td>\n",
|
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" <td>K0</td>\n",
|
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" <td>K0</td>\n",
|
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" <td>C0</td>\n",
|
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" <td>D0</td>\n",
|
|
" </tr>\n",
|
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" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>A2</td>\n",
|
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" <td>B2</td>\n",
|
|
" <td>K1</td>\n",
|
|
" <td>K0</td>\n",
|
|
" <td>C1</td>\n",
|
|
" <td>D1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>A2</td>\n",
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|
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"pd.merge(left, right, how='left', on=['key1', 'key2'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Joining\n",
|
|
"Joining is a convenient method for combining the columns of two potentially differently-indexed DataFrames into a single result DataFrame."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
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"execution_count": 46,
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|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],\n",
|
|
" 'B': ['B0', 'B1', 'B2']},\n",
|
|
" index=['K0', 'K1', 'K2']) \n",
|
|
"\n",
|
|
"right = pd.DataFrame({'C': ['C0', 'C2', 'C3'],\n",
|
|
" 'D': ['D0', 'D2', 'D3']},\n",
|
|
" index=['K0', 'K2', 'K3'])"
|
|
]
|
|
},
|
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|
|
"cell_type": "code",
|
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"execution_count": 47,
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"metadata": {
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|
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|
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|
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|
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" <td>D2</td>\n",
|
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"metadata": {},
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}
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],
|
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|
|
"left.join(right)"
|
|
]
|
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},
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|
|
"cell_type": "code",
|
|
"execution_count": 48,
|
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|
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"collapsed": false
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},
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"outputs": [
|
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|
|
"data": {
|
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"text/html": [
|
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"<div>\n",
|
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"<table border=\"1\" class=\"dataframe\">\n",
|
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|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>A</th>\n",
|
|
" <th>B</th>\n",
|
|
" <th>C</th>\n",
|
|
" <th>D</th>\n",
|
|
" </tr>\n",
|
|
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|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>K0</th>\n",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
" <th>K1</th>\n",
|
|
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|
|
" <td>B1</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>K2</th>\n",
|
|
" <td>A2</td>\n",
|
|
" <td>B2</td>\n",
|
|
" <td>C2</td>\n",
|
|
" <td>D2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>K3</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>C3</td>\n",
|
|
" <td>D3</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
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"</table>\n",
|
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"</div>"
|
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],
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|
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" A B C D\n",
|
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"K0 A0 B0 C0 D0\n",
|
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"K1 A1 B1 NaN NaN\n",
|
|
"K2 A2 B2 C2 D2\n",
|
|
"K3 NaN NaN C3 D3"
|
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]
|
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},
|
|
"execution_count": 48,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
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}
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],
|
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"source": [
|
|
"left.join(right, how='outer')"
|
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]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Great Job!"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
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"display_name": "Python 3",
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}
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