1071 lines
22 KiB
Plaintext
1071 lines
22 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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"# Operations\n",
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"\n",
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"There are lots of operations with pandas that will be really useful to you, but don't fall into any distinct category. Let's show them here in this lecture:"
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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": 52,
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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",
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" <th></th>\n",
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" <th>col1</th>\n",
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" <th>col2</th>\n",
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" <th>col3</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>444</td>\n",
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" <td>abc</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>555</td>\n",
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" <td>def</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>666</td>\n",
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" <td>ghi</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>4</td>\n",
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" <td>444</td>\n",
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" <td>xyz</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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"text/plain": [
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" col1 col2 col3\n",
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"0 1 444 abc\n",
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"1 2 555 def\n",
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"2 3 666 ghi\n",
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"3 4 444 xyz"
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]
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},
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"execution_count": 52,
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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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"import pandas as pd\n",
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"df = pd.DataFrame({'col1':[1,2,3,4],'col2':[444,555,666,444],'col3':['abc','def','ghi','xyz']})\n",
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"df.head()"
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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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"### Info on Unique Values"
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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": 53,
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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/plain": [
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"array([444, 555, 666])"
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]
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},
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"execution_count": 53,
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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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"df['col2'].unique()"
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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": 54,
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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/plain": [
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"3"
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]
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},
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"execution_count": 54,
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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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"df['col2'].nunique()"
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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": 55,
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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/plain": [
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"444 2\n",
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"555 1\n",
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"666 1\n",
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"Name: col2, dtype: int64"
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]
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},
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"execution_count": 55,
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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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"df['col2'].value_counts()"
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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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"### Selecting Data"
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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": 56,
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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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"#Select from DataFrame using criteria from multiple columns\n",
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"newdf = df[(df['col1']>2) & (df['col2']==444)]"
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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": 57,
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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",
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" <th></th>\n",
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" <th>col1</th>\n",
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" <th>col2</th>\n",
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" <th>col3</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>3</th>\n",
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" <td>4</td>\n",
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" <td>444</td>\n",
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" <td>xyz</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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"text/plain": [
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" col1 col2 col3\n",
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"3 4 444 xyz"
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]
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},
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"execution_count": 57,
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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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"newdf"
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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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"### Applying Functions"
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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": 58,
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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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"def times2(x):\n",
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" return x*2"
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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": 59,
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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/plain": [
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"0 2\n",
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"1 4\n",
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"2 6\n",
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"3 8\n",
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"Name: col1, dtype: int64"
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]
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},
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"execution_count": 59,
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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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"df['col1'].apply(times2)"
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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": 60,
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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/plain": [
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"0 3\n",
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"1 3\n",
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"2 3\n",
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"3 3\n",
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"Name: col3, dtype: int64"
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]
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},
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"execution_count": 60,
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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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"df['col3'].apply(len)"
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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": 61,
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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/plain": [
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"10"
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]
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},
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"execution_count": 61,
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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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"df['col1'].sum()"
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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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"** Permanently Removing a Column**"
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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": 62,
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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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"del df['col1']"
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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": 63,
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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",
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" <th></th>\n",
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" <th>col2</th>\n",
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" <th>col3</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>444</td>\n",
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" <td>abc</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>555</td>\n",
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" <td>def</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>666</td>\n",
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" <td>ghi</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>444</td>\n",
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" <td>xyz</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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"text/plain": [
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" col2 col3\n",
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"0 444 abc\n",
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"1 555 def\n",
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"2 666 ghi\n",
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"3 444 xyz"
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]
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},
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"execution_count": 63,
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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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"df"
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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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"** Get column and index names: **"
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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": 64,
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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/plain": [
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"Index(['col2', 'col3'], dtype='object')"
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]
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},
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"execution_count": 64,
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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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"df.columns"
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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": 65,
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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/plain": [
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"RangeIndex(start=0, stop=4, step=1)"
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]
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},
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"execution_count": 65,
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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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"df.index"
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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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"** Sorting and Ordering a DataFrame:**"
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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": 66,
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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",
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" <th></th>\n",
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" <th>col2</th>\n",
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" <th>col3</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>444</td>\n",
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" <td>abc</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>555</td>\n",
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" <td>def</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>666</td>\n",
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" <td>ghi</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>3</th>\n",
|
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" <td>444</td>\n",
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" <td>xyz</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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" col2 col3\n",
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"3 444 xyz"
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"source": [
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"df"
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},
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{
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"cell_type": "code",
|
|
"execution_count": 67,
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|
"metadata": {
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"collapsed": false
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},
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"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>col2</th>\n",
|
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" <th>col3</th>\n",
|
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" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
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" <td>444</td>\n",
|
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" <td>abc</td>\n",
|
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" </tr>\n",
|
|
" <tr>\n",
|
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" <th>3</th>\n",
|
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" <td>444</td>\n",
|
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" <td>xyz</td>\n",
|
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" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>555</td>\n",
|
|
" <td>def</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
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" <td>666</td>\n",
|
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" <td>ghi</td>\n",
|
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" </tr>\n",
|
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" </tbody>\n",
|
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"</table>\n",
|
|
"</div>"
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],
|
|
"text/plain": [
|
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" col2 col3\n",
|
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"0 444 abc\n",
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"3 444 xyz\n",
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"1 555 def\n",
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"2 666 ghi"
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]
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},
|
|
"execution_count": 67,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.sort_values(by='col2') #inplace=False by default"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"** Find Null Values or Check for Null Values**"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 68,
|
|
"metadata": {
|
|
"collapsed": false
|
|
},
|
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"outputs": [
|
|
{
|
|
"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",
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" <th></th>\n",
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" <th>col2</th>\n",
|
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" <th>col3</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>False</td>\n",
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" <td>False</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>False</td>\n",
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" <td>False</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>False</td>\n",
|
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" <td>False</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
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" <th>3</th>\n",
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" <td>False</td>\n",
|
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" <td>False</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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"text/plain": [
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" col2 col3\n",
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"0 False False\n",
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"1 False False\n",
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"2 False False\n",
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"3 False False"
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]
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},
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"execution_count": 68,
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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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"df.isnull()"
|
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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": 69,
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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",
|
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" <th></th>\n",
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" <th>col2</th>\n",
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" <th>col3</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>444</td>\n",
|
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" <td>abc</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>555</td>\n",
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" <td>def</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>666</td>\n",
|
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" <td>ghi</td>\n",
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" </tr>\n",
|
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" <tr>\n",
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" <th>3</th>\n",
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" <td>444</td>\n",
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" <td>xyz</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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"text/plain": [
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" col2 col3\n",
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"0 444 abc\n",
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"1 555 def\n",
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"2 666 ghi\n",
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"3 444 xyz"
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]
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},
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"execution_count": 69,
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
|
],
|
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"source": [
|
|
"# Drop rows with NaN Values\n",
|
|
"df.dropna()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"** Filling in NaN values with something else: **"
|
|
]
|
|
},
|
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{
|
|
"cell_type": "code",
|
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"execution_count": 71,
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"metadata": {
|
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"collapsed": true
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},
|
|
"outputs": [],
|
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"source": [
|
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"import numpy as np"
|
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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": 72,
|
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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",
|
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" <th></th>\n",
|
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" <th>col1</th>\n",
|
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" <th>col2</th>\n",
|
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" <th>col3</th>\n",
|
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" </tr>\n",
|
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" </thead>\n",
|
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" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
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" <td>1.0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>abc</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
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" <th>1</th>\n",
|
|
" <td>2.0</td>\n",
|
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" <td>555.0</td>\n",
|
|
" <td>def</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>3.0</td>\n",
|
|
" <td>666.0</td>\n",
|
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" <td>ghi</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>NaN</td>\n",
|
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" <td>444.0</td>\n",
|
|
" <td>xyz</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
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],
|
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"text/plain": [
|
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" col1 col2 col3\n",
|
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"0 1.0 NaN abc\n",
|
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"1 2.0 555.0 def\n",
|
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"2 3.0 666.0 ghi\n",
|
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"3 NaN 444.0 xyz"
|
|
]
|
|
},
|
|
"execution_count": 72,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df = pd.DataFrame({'col1':[1,2,3,np.nan],\n",
|
|
" 'col2':[np.nan,555,666,444],\n",
|
|
" 'col3':['abc','def','ghi','xyz']})\n",
|
|
"df.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 75,
|
|
"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>col1</th>\n",
|
|
" <th>col2</th>\n",
|
|
" <th>col3</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>1</td>\n",
|
|
" <td>FILL</td>\n",
|
|
" <td>abc</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>2</td>\n",
|
|
" <td>555</td>\n",
|
|
" <td>def</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>3</td>\n",
|
|
" <td>666</td>\n",
|
|
" <td>ghi</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>FILL</td>\n",
|
|
" <td>444</td>\n",
|
|
" <td>xyz</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" col1 col2 col3\n",
|
|
"0 1 FILL abc\n",
|
|
"1 2 555 def\n",
|
|
"2 3 666 ghi\n",
|
|
"3 FILL 444 xyz"
|
|
]
|
|
},
|
|
"execution_count": 75,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.fillna('FILL')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 89,
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"data = {'A':['foo','foo','foo','bar','bar','bar'],\n",
|
|
" 'B':['one','one','two','two','one','one'],\n",
|
|
" 'C':['x','y','x','y','x','y'],\n",
|
|
" 'D':[1,3,2,5,4,1]}\n",
|
|
"\n",
|
|
"df = pd.DataFrame(data)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 90,
|
|
"metadata": {
|
|
"collapsed": false
|
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},
|
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"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>C</th>\n",
|
|
" <th>D</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>foo</td>\n",
|
|
" <td>one</td>\n",
|
|
" <td>x</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>foo</td>\n",
|
|
" <td>one</td>\n",
|
|
" <td>y</td>\n",
|
|
" <td>3</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>foo</td>\n",
|
|
" <td>two</td>\n",
|
|
" <td>x</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>bar</td>\n",
|
|
" <td>two</td>\n",
|
|
" <td>y</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>bar</td>\n",
|
|
" <td>one</td>\n",
|
|
" <td>x</td>\n",
|
|
" <td>4</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>bar</td>\n",
|
|
" <td>one</td>\n",
|
|
" <td>y</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" A B C D\n",
|
|
"0 foo one x 1\n",
|
|
"1 foo one y 3\n",
|
|
"2 foo two x 2\n",
|
|
"3 bar two y 5\n",
|
|
"4 bar one x 4\n",
|
|
"5 bar one y 1"
|
|
]
|
|
},
|
|
"execution_count": 90,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 91,
|
|
"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>C</th>\n",
|
|
" <th>x</th>\n",
|
|
" <th>y</th>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>A</th>\n",
|
|
" <th>B</th>\n",
|
|
" <th></th>\n",
|
|
" <th></th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th rowspan=\"2\" valign=\"top\">bar</th>\n",
|
|
" <th>one</th>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>two</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>5.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th rowspan=\"2\" valign=\"top\">foo</th>\n",
|
|
" <th>one</th>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>3.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>two</th>\n",
|
|
" <td>2.0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
"C x y\n",
|
|
"A B \n",
|
|
"bar one 4.0 1.0\n",
|
|
" two NaN 5.0\n",
|
|
"foo one 1.0 3.0\n",
|
|
" two 2.0 NaN"
|
|
]
|
|
},
|
|
"execution_count": 91,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.pivot_table(values='D',index=['A', 'B'],columns=['C'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Great Job!"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.5.1"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
}
|