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data-science-ipython-notebooks/pandas/pandas_clean.ipynb
Donne Martin ad82bdeefc Cleaned up notebook.
2015-04-10 11:03:00 -04:00

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{
"metadata": {
"name": "",
"signature": "sha256:b619f1fd1f2d4495d6a2fe9d048c09b7319b119d4e10a5b2348f0ac6f380a27c"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Pandas Cleaning\n",
"* Replace\n",
"* Drop\n",
"* Concatenate"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from pandas import Series, DataFrame\n",
"import pandas as pd"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Setup a DataFrame:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data_1 = {'state' : ['VA', 'VA', 'VA', 'MD', 'MD'],\n",
" 'year' : [2012, 2013, 2014, 2014, 2015],\n",
" 'population' : [5.0, 5.1, 5.2, 4.0, 4.1]}\n",
"df_1 = DataFrame(data_1)\n",
"df_1"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>population</th>\n",
" <th>state</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 5.0</td>\n",
" <td> VA</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 5.1</td>\n",
" <td> VA</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 5.2</td>\n",
" <td> VA</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 4.0</td>\n",
" <td> MD</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 4.1</td>\n",
" <td> MD</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
" population state year\n",
"0 5.0 VA 2012\n",
"1 5.1 VA 2013\n",
"2 5.2 VA 2014\n",
"3 4.0 MD 2014\n",
"4 4.1 MD 2015"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Replace"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Replace all occurrences of a string with another string, in place (no copy):"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df_1.replace('VA', 'VIRGINIA', inplace=True)\n",
"df_1"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>population</th>\n",
" <th>state</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 5.0</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 5.1</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 5.2</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 4.0</td>\n",
" <td> MD</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 4.1</td>\n",
" <td> MD</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
" population state year\n",
"0 5.0 VIRGINIA 2012\n",
"1 5.1 VIRGINIA 2013\n",
"2 5.2 VIRGINIA 2014\n",
"3 4.0 MD 2014\n",
"4 4.1 MD 2015"
]
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In a specified column, replace all occurrences of a string with another string, in place (no copy):"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df_1.replace({'state' : { 'MD' : 'MARYLAND' }}, inplace=True)\n",
"df_1"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>population</th>\n",
" <th>state</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 5.0</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 5.1</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 5.2</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 4.0</td>\n",
" <td> MARYLAND</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 4.1</td>\n",
" <td> MARYLAND</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
" population state year\n",
"0 5.0 VIRGINIA 2012\n",
"1 5.1 VIRGINIA 2013\n",
"2 5.2 VIRGINIA 2014\n",
"3 4.0 MARYLAND 2014\n",
"4 4.1 MARYLAND 2015"
]
}
],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Drop"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Drop the 'population' column and return a copy of the DataFrame:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df_2 = df_1.drop('population', axis=1)\n",
"df_2"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>state</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> VIRGINIA</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> VIRGINIA</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> VIRGINIA</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> MARYLAND</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> MARYLAND</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
" state year\n",
"0 VIRGINIA 2012\n",
"1 VIRGINIA 2013\n",
"2 VIRGINIA 2014\n",
"3 MARYLAND 2014\n",
"4 MARYLAND 2015"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Concatenate"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Concatenate two DataFrames:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data_2 = {'state' : ['NY', 'NY', 'NY', 'FL', 'FL'],\n",
" 'year' : [2012, 2013, 2014, 2014, 2015],\n",
" 'population' : [6.0, 6.1, 6.2, 3.0, 3.1]}\n",
"df_3 = DataFrame(data_2)\n",
"df_3"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>population</th>\n",
" <th>state</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 6.0</td>\n",
" <td> NY</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 6.1</td>\n",
" <td> NY</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 6.2</td>\n",
" <td> NY</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 3.0</td>\n",
" <td> FL</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 3.1</td>\n",
" <td> FL</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": [
" population state year\n",
"0 6.0 NY 2012\n",
"1 6.1 NY 2013\n",
"2 6.2 NY 2014\n",
"3 3.0 FL 2014\n",
"4 3.1 FL 2015"
]
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df_4 = pd.concat([df_1, df_3])\n",
"df_4"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>population</th>\n",
" <th>state</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 5.0</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 5.1</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 5.2</td>\n",
" <td> VIRGINIA</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 4.0</td>\n",
" <td> MARYLAND</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 4.1</td>\n",
" <td> MARYLAND</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 6.0</td>\n",
" <td> NY</td>\n",
" <td> 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 6.1</td>\n",
" <td> NY</td>\n",
" <td> 2013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 6.2</td>\n",
" <td> NY</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 3.0</td>\n",
" <td> FL</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 3.1</td>\n",
" <td> FL</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 8,
"text": [
" population state year\n",
"0 5.0 VIRGINIA 2012\n",
"1 5.1 VIRGINIA 2013\n",
"2 5.2 VIRGINIA 2014\n",
"3 4.0 MARYLAND 2014\n",
"4 4.1 MARYLAND 2015\n",
"0 6.0 NY 2012\n",
"1 6.1 NY 2013\n",
"2 6.2 NY 2014\n",
"3 3.0 FL 2014\n",
"4 3.1 FL 2015"
]
}
],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
}
],
"metadata": {}
}
]
}
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