diff --git a/pandas/pandas_clean.ipynb b/pandas/pandas_clean.ipynb
index 88efc19..fec0430 100644
--- a/pandas/pandas_clean.ipynb
+++ b/pandas/pandas_clean.ipynb
@@ -1,569 +1,591 @@
{
- "metadata": {
- "name": "",
- "signature": "sha256:b619f1fd1f2d4495d6a2fe9d048c09b7319b119d4e10a5b2348f0ac6f380a27c"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
+ "cells": [
{
- "cells": [
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Pandas Cleaning\n",
+ "* Replace\n",
+ "* Drop\n",
+ "* Concatenate"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "from pandas import Series, DataFrame\n",
+ "import pandas as pd"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Setup a DataFrame:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "markdown",
+ "data": {
+ "text/html": [
+ "
\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " population | \n",
+ " state | \n",
+ " year | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 5.0 | \n",
+ " VA | \n",
+ " 2012 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 5.1 | \n",
+ " VA | \n",
+ " 2013 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 5.2 | \n",
+ " VA | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 4.0 | \n",
+ " MD | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 4.1 | \n",
+ " MD | \n",
+ " 2015 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " 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"
+ ]
+ },
+ "execution_count": 2,
"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": [
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " population | \n",
- " state | \n",
- " year | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " 0 | \n",
- " 5.0 | \n",
- " VA | \n",
- " 2012 | \n",
- "
\n",
- " \n",
- " 1 | \n",
- " 5.1 | \n",
- " VA | \n",
- " 2013 | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " 5.2 | \n",
- " VA | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " 4.0 | \n",
- " MD | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " 4.1 | \n",
- " MD | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "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": [
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " population | \n",
- " state | \n",
- " year | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " 0 | \n",
- " 5.0 | \n",
- " VIRGINIA | \n",
- " 2012 | \n",
- "
\n",
- " \n",
- " 1 | \n",
- " 5.1 | \n",
- " VIRGINIA | \n",
- " 2013 | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " 5.2 | \n",
- " VIRGINIA | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " 4.0 | \n",
- " MD | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " 4.1 | \n",
- " MD | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "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": [
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " population | \n",
- " state | \n",
- " year | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " 0 | \n",
- " 5.0 | \n",
- " VIRGINIA | \n",
- " 2012 | \n",
- "
\n",
- " \n",
- " 1 | \n",
- " 5.1 | \n",
- " VIRGINIA | \n",
- " 2013 | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " 5.2 | \n",
- " VIRGINIA | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " 4.0 | \n",
- " MARYLAND | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " 4.1 | \n",
- " MARYLAND | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "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": [
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " state | \n",
- " year | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " 0 | \n",
- " VIRGINIA | \n",
- " 2012 | \n",
- "
\n",
- " \n",
- " 1 | \n",
- " VIRGINIA | \n",
- " 2013 | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " VIRGINIA | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " MARYLAND | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " MARYLAND | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "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": [
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " population | \n",
- " state | \n",
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- "
\n",
- " \n",
- " \n",
- " \n",
- " 0 | \n",
- " 6.0 | \n",
- " NY | \n",
- " 2012 | \n",
- "
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- " \n",
- " 1 | \n",
- " 6.1 | \n",
- " NY | \n",
- " 2013 | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " 6.2 | \n",
- " NY | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " 3.0 | \n",
- " FL | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " 3.1 | \n",
- " FL | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "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": [
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " population | \n",
- " state | \n",
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- "
\n",
- " \n",
- " \n",
- " \n",
- " 0 | \n",
- " 5.0 | \n",
- " VIRGINIA | \n",
- " 2012 | \n",
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- " \n",
- " 1 | \n",
- " 5.1 | \n",
- " VIRGINIA | \n",
- " 2013 | \n",
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- " \n",
- " 2 | \n",
- " 5.2 | \n",
- " VIRGINIA | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " 4.0 | \n",
- " MARYLAND | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " 4.1 | \n",
- " MARYLAND | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- " 0 | \n",
- " 6.0 | \n",
- " NY | \n",
- " 2012 | \n",
- "
\n",
- " \n",
- " 1 | \n",
- " 6.1 | \n",
- " NY | \n",
- " 2013 | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " 6.2 | \n",
- " NY | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " 3.0 | \n",
- " FL | \n",
- " 2014 | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " 3.1 | \n",
- " FL | \n",
- " 2015 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "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
+ "output_type": "execute_result"
}
],
- "metadata": {}
+ "source": [
+ "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"
+ ]
+ },
+ {
+ "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",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " population | \n",
+ " state | \n",
+ " year | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 5.0 | \n",
+ " VIRGINIA | \n",
+ " 2012 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 5.1 | \n",
+ " VIRGINIA | \n",
+ " 2013 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 5.2 | \n",
+ " VIRGINIA | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 4.0 | \n",
+ " MD | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 4.1 | \n",
+ " MD | \n",
+ " 2015 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " 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"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df_1.replace('VA', 'VIRGINIA', inplace=True)\n",
+ "df_1"
+ ]
+ },
+ {
+ "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",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " population | \n",
+ " state | \n",
+ " year | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 5.0 | \n",
+ " VIRGINIA | \n",
+ " 2012 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 5.1 | \n",
+ " VIRGINIA | \n",
+ " 2013 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 5.2 | \n",
+ " VIRGINIA | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 4.0 | \n",
+ " MARYLAND | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 4.1 | \n",
+ " MARYLAND | \n",
+ " 2015 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " 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"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df_1.replace({'state' : { 'MD' : 'MARYLAND' }}, inplace=True)\n",
+ "df_1"
+ ]
+ },
+ {
+ "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",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " state | \n",
+ " year | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " VIRGINIA | \n",
+ " 2012 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " VIRGINIA | \n",
+ " 2013 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " VIRGINIA | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " MARYLAND | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " MARYLAND | \n",
+ " 2015 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " state year\n",
+ "0 VIRGINIA 2012\n",
+ "1 VIRGINIA 2013\n",
+ "2 VIRGINIA 2014\n",
+ "3 MARYLAND 2014\n",
+ "4 MARYLAND 2015"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df_2 = df_1.drop('population', axis=1)\n",
+ "df_2"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Concatenate"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Concatenate two DataFrames:"
+ ]
+ },
+ {
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+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
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\n",
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+ " 6.0 | \n",
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+ "4 3.1 FL 2015"
+ ]
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+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
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+ "source": [
+ "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"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
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+ "data": {
+ "text/html": [
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+ " 4.0 | \n",
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+ " population state year\n",
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+ "execution_count": 8,
+ "metadata": {},
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+ "df_4 = pd.concat([df_1, df_3])\n",
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+ "cell_type": "code",
+ "execution_count": 8,
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