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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[Back to the GitHub repository](https://github.com/rasbt/python_reference)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load_ext watermark\n",
      "%watermark -a 'Sebastian Raschka' -v -d -p pandas"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Sebastian Raschka 28/01/2015 \n",
        "\n",
        "CPython 3.4.2\n",
        "IPython 2.3.1\n",
        "\n",
        "pandas 0.15.2\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<font size=\"1.5em\">[More information](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/ipython_magic/watermark.ipynb) about the `watermark` magic command extension.</font>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Things in Pandas I Wish I'd Had Known Earlier"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is just a small but growing collection of pandas snippets that I find occasionally and particularly useful -- consider it as my personal notebook. Suggestions, tips, and contributions are very, very welcome!"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Sections"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "- [Loading Some Example Data](#Loading-Some-Example-Data)\n",
      "- [Renaming Columns](#Renaming-Columns)\n",
      "    - [Converting Column Names to Lowercase](#Converting-Column-Names-to-Lowercase)\n",
      "    - [Renaming Particular Columns](#Renaming-Particular-Columns)\n",
      "- [Applying Computations Rows-wise](#Applying-Computations-Rows-wise)\n",
      "    - [Changing Values in a Column](#Changing-Values-in-a-Column)\n",
      "    - [Adding a New Column](#Adding-a-New-Column)\n",
      "    - [Applying Functions to Multiple Columns](#Applying-Functions-to-Multiple-Columns)\n",
      "- [Missing Values aka NaNs](#Missing-Values-aka-NaNs)\n",
      "    - [Counting Rows with NaNs](#Counting-Rows-with-NaNs)\n",
      "    - [Selecting NaN Rows](#Selecting-NaN-Rows)\n",
      "    - [Selecting non-NaN Rows](#Selecting-non-NaN-Rows)\n",
      "    - [Filling NaN Rows](#Filling-NaN-Rows)\n",
      "- [Appending Rows to a DataFrame](#Appending-Rows-to-a-DataFrame)\n",
      "- [Sorting and Reindexing DataFrames](#Sorting-and-Reindexing-DataFrames)\n",
      "- [Updating Columns](#Updating-Columns)\n",
      "- [Chaining Conditions - Using Bitwise Operators](#Chaining-Conditions---Using-Bitwise-Operators)\n",
      "- [Column Types](#Column-Types)\n",
      "    - [Printing Column Types](#Printing-Column-Types)\n",
      "    - [Selecting by Column Type](#Selecting-by-Column-Type)\n",
      "    - [Converting Column Types](#Converting-Column-Types)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Loading Some Example Data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I am heavily into sports prediction (via a machine learning approach) these days. So, let us use a (very) small subset of the soccer data that I am just working with."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "\n",
      "df = pd.read_csv('https://raw.githubusercontent.com/rasbt/python_reference/master/Data/some_soccer_data.csv')\n",
      "df"
     ],
     "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>PLAYER</th>\n",
        "      <th>SALARY</th>\n",
        "      <th>GP</th>\n",
        "      <th>G</th>\n",
        "      <th>A</th>\n",
        "      <th>SOT</th>\n",
        "      <th>PPG</th>\n",
        "      <th>P</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>     Sergio Ag\u00fcero\\n Forward \u2014 Manchester City</td>\n",
        "      <td> $19.2m</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td>  3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>              Eden Hazard\\n Midfield \u2014 Chelsea</td>\n",
        "      <td> $18.9m</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td>  4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>            Alexis S\u00e1nchez\\n Forward \u2014 Arsenal</td>\n",
        "      <td> $17.6m</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 12</td>\n",
        "      <td>  7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>       Yaya Tour\u00e9\\n Midfield \u2014 Manchester City</td>\n",
        "      <td> $16.6m</td>\n",
        "      <td> 18</td>\n",
        "      <td>  7</td>\n",
        "      <td>  1</td>\n",
        "      <td> 19</td>\n",
        "      <td> 10.99</td>\n",
        "      <td> 197.91</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> \u00c1ngel Di Mar\u00eda\\n Midfield \u2014 Manchester United</td>\n",
        "      <td> $15.0m</td>\n",
        "      <td> 13</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> 10.17</td>\n",
        "      <td> 132.23</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>         Santiago Cazorla\\n Midfield \u2014 Arsenal</td>\n",
        "      <td> $14.8m</td>\n",
        "      <td> 20</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td>  9.97</td>\n",
        "      <td>    NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>      David Silva\\n Midfield \u2014 Manchester City</td>\n",
        "      <td> $14.3m</td>\n",
        "      <td> 15</td>\n",
        "      <td>  6</td>\n",
        "      <td>  2</td>\n",
        "      <td> 11</td>\n",
        "      <td> 10.35</td>\n",
        "      <td> 155.26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>            Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea</td>\n",
        "      <td> $14.0m</td>\n",
        "      <td> 20</td>\n",
        "      <td>  2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>          Saido Berahino\\n Forward \u2014 West Brom</td>\n",
        "      <td> $13.8m</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>         Steven Gerrard\\n Midfield \u2014 Liverpool</td>\n",
        "      <td> $13.8m</td>\n",
        "      <td> 20</td>\n",
        "      <td>  5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "                                          PLAYER  SALARY  GP   G   A  SOT  \\\n",
        "0      Sergio Ag\u00fcero\\n Forward \u2014 Manchester City  $19.2m  16  14   3   34   \n",
        "1               Eden Hazard\\n Midfield \u2014 Chelsea  $18.9m  21   8   4   17   \n",
        "2             Alexis S\u00e1nchez\\n Forward \u2014 Arsenal  $17.6m NaN  12   7   29   \n",
        "3        Yaya Tour\u00e9\\n Midfield \u2014 Manchester City  $16.6m  18   7   1   19   \n",
        "4  \u00c1ngel Di Mar\u00eda\\n Midfield \u2014 Manchester United  $15.0m  13   3 NaN   13   \n",
        "5          Santiago Cazorla\\n Midfield \u2014 Arsenal  $14.8m  20   4 NaN   20   \n",
        "6       David Silva\\n Midfield \u2014 Manchester City  $14.3m  15   6   2   11   \n",
        "7             Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea  $14.0m  20   2  14   10   \n",
        "8           Saido Berahino\\n Forward \u2014 West Brom  $13.8m  21   9   0   20   \n",
        "9          Steven Gerrard\\n Midfield \u2014 Liverpool  $13.8m  20   5   1   11   \n",
        "\n",
        "     PPG       P  \n",
        "0  13.12  209.98  \n",
        "1  13.05  274.04  \n",
        "2  11.19  223.86  \n",
        "3  10.99  197.91  \n",
        "4  10.17  132.23  \n",
        "5   9.97     NaN  \n",
        "6  10.35  155.26  \n",
        "7  10.47  209.49  \n",
        "8   7.02  147.43  \n",
        "9   7.50  150.01  "
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Renaming Columns"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Converting Column Names to Lowercase"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Converting column names to lowercase\n",
      "\n",
      "df.columns = [c.lower() for c in df.columns]\n",
      "\n",
      "# or\n",
      "# df.rename(columns=lambda x : x.lower())\n",
      "\n",
      "df.tail(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>gp</th>\n",
        "      <th>g</th>\n",
        "      <th>a</th>\n",
        "      <th>sot</th>\n",
        "      <th>ppg</th>\n",
        "      <th>p</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>    Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea</td>\n",
        "      <td> $14.0m</td>\n",
        "      <td> 20</td>\n",
        "      <td> 2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>  Saido Berahino\\n Forward \u2014 West Brom</td>\n",
        "      <td> $13.8m</td>\n",
        "      <td> 21</td>\n",
        "      <td> 9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> Steven Gerrard\\n Midfield \u2014 Liverpool</td>\n",
        "      <td> $13.8m</td>\n",
        "      <td> 20</td>\n",
        "      <td> 5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "                                  player  salary  gp  g   a  sot    ppg  \\\n",
        "7     Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea  $14.0m  20  2  14   10  10.47   \n",
        "8   Saido Berahino\\n Forward \u2014 West Brom  $13.8m  21  9   0   20   7.02   \n",
        "9  Steven Gerrard\\n Midfield \u2014 Liverpool  $13.8m  20  5   1   11   7.50   \n",
        "\n",
        "        p  \n",
        "7  209.49  \n",
        "8  147.43  \n",
        "9  150.01  "
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Renaming Particular Columns"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = df.rename(columns={'p': 'points', \n",
      "                        'gp': 'games',\n",
      "                        'sot': 'shots_on_target',\n",
      "                        'g': 'goals',\n",
      "                        'ppg': 'points_per_game',\n",
      "                        'a': 'assists',})\n",
      "\n",
      "df.tail(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>    Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea</td>\n",
        "      <td> $14.0m</td>\n",
        "      <td> 20</td>\n",
        "      <td> 2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>  Saido Berahino\\n Forward \u2014 West Brom</td>\n",
        "      <td> $13.8m</td>\n",
        "      <td> 21</td>\n",
        "      <td> 9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> Steven Gerrard\\n Midfield \u2014 Liverpool</td>\n",
        "      <td> $13.8m</td>\n",
        "      <td> 20</td>\n",
        "      <td> 5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "                                  player  salary  games  goals  assists  \\\n",
        "7     Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea  $14.0m     20      2       14   \n",
        "8   Saido Berahino\\n Forward \u2014 West Brom  $13.8m     21      9        0   \n",
        "9  Steven Gerrard\\n Midfield \u2014 Liverpool  $13.8m     20      5        1   \n",
        "\n",
        "   shots_on_target  points_per_game  points  \n",
        "7               10            10.47  209.49  \n",
        "8               20             7.02  147.43  \n",
        "9               11             7.50  150.01  "
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Applying Computations Rows-wise"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Changing Values in a Column"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Processing `salary` column\n",
      "\n",
      "df['salary'] = df['salary'].apply(lambda x: x.strip('$m'))\n",
      "df.tail()"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>    Santiago Cazorla\\n Midfield \u2014 Arsenal</td>\n",
        "      <td> 14.8</td>\n",
        "      <td> 20</td>\n",
        "      <td> 4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td>  9.97</td>\n",
        "      <td>    NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td> David Silva\\n Midfield \u2014 Manchester City</td>\n",
        "      <td> 14.3</td>\n",
        "      <td> 15</td>\n",
        "      <td> 6</td>\n",
        "      <td>  2</td>\n",
        "      <td> 11</td>\n",
        "      <td> 10.35</td>\n",
        "      <td> 155.26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>       Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea</td>\n",
        "      <td> 14.0</td>\n",
        "      <td> 20</td>\n",
        "      <td> 2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>     Saido Berahino\\n Forward \u2014 West Brom</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td> 9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>    Steven Gerrard\\n Midfield \u2014 Liverpool</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td> 5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "                                     player salary  games  goals  assists  \\\n",
        "5     Santiago Cazorla\\n Midfield \u2014 Arsenal   14.8     20      4      NaN   \n",
        "6  David Silva\\n Midfield \u2014 Manchester City   14.3     15      6        2   \n",
        "7        Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea   14.0     20      2       14   \n",
        "8      Saido Berahino\\n Forward \u2014 West Brom   13.8     21      9        0   \n",
        "9     Steven Gerrard\\n Midfield \u2014 Liverpool   13.8     20      5        1   \n",
        "\n",
        "   shots_on_target  points_per_game  points  \n",
        "5               20             9.97     NaN  \n",
        "6               11            10.35  155.26  \n",
        "7               10            10.47  209.49  \n",
        "8               20             7.02  147.43  \n",
        "9               11             7.50  150.01  "
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Adding a New Column"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['team'] = pd.Series('', index=df.index)\n",
      "\n",
      "# or\n",
      "df.insert(loc=8, column='position', value='') \n",
      "\n",
      "df.tail(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>    Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea</td>\n",
        "      <td> 14.0</td>\n",
        "      <td> 20</td>\n",
        "      <td> 2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "      <td> </td>\n",
        "      <td> </td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>  Saido Berahino\\n Forward \u2014 West Brom</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td> 9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td> </td>\n",
        "      <td> </td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> Steven Gerrard\\n Midfield \u2014 Liverpool</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td> 5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "      <td> </td>\n",
        "      <td> </td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "                                  player salary  games  goals  assists  \\\n",
        "7     Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea   14.0     20      2       14   \n",
        "8   Saido Berahino\\n Forward \u2014 West Brom   13.8     21      9        0   \n",
        "9  Steven Gerrard\\n Midfield \u2014 Liverpool   13.8     20      5        1   \n",
        "\n",
        "   shots_on_target  points_per_game  points position team  \n",
        "7               10            10.47  209.49                \n",
        "8               20             7.02  147.43                \n",
        "9               11             7.50  150.01                "
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Processing `player` column\n",
      "\n",
      "def process_player_col(text):\n",
      "    name, rest = text.split('\\n')\n",
      "    position, team = [x.strip() for x in rest.split(' \u2014 ')]\n",
      "    return pd.Series([name, team, position])\n",
      "\n",
      "df[['player', 'team', 'position']] = df.player.apply(process_player_col)\n",
      "\n",
      "# modified after tip from reddit.com/user/hharison\n",
      "#\n",
      "# Alternative (inferior) approach:\n",
      "#\n",
      "#for idx,row in df.iterrows():\n",
      "#    name, position, team = process_player_col(row['player'])\n",
      "#    df.ix[idx, 'player'], df.ix[idx, 'position'], df.ix[idx, 'team'] = name, position, team\n",
      "    \n",
      "df.tail(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>  Cesc F\u00e0bregas</td>\n",
        "      <td> 14.0</td>\n",
        "      <td> 20</td>\n",
        "      <td> 2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "      <td> Midfield</td>\n",
        "      <td>   Chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td> Saido Berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td> 9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  Forward</td>\n",
        "      <td> West Brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> Steven Gerrard</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td> 5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "      <td> Midfield</td>\n",
        "      <td> Liverpool</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "7   Cesc F\u00e0bregas   14.0     20      2       14               10   \n",
        "8  Saido Berahino   13.8     21      9        0               20   \n",
        "9  Steven Gerrard   13.8     20      5        1               11   \n",
        "\n",
        "   points_per_game  points  position       team  \n",
        "7            10.47  209.49  Midfield    Chelsea  \n",
        "8             7.02  147.43   Forward  West Brom  \n",
        "9             7.50  150.01  Midfield  Liverpool  "
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Applying Functions to Multiple Columns"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cols = ['player', 'position', 'team']\n",
      "df[cols] = df[cols].applymap(lambda x: x.lower())\n",
      "df.head()"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td> 19.2</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td>  3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td>  forward</td>\n",
        "      <td>   manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td>  4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "      <td> midfield</td>\n",
        "      <td>           chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td> 17.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 12</td>\n",
        "      <td>  7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td>  forward</td>\n",
        "      <td>           arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>     yaya tour\u00e9</td>\n",
        "      <td> 16.6</td>\n",
        "      <td> 18</td>\n",
        "      <td>  7</td>\n",
        "      <td>  1</td>\n",
        "      <td> 19</td>\n",
        "      <td> 10.99</td>\n",
        "      <td> 197.91</td>\n",
        "      <td> midfield</td>\n",
        "      <td>   manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> \u00e1ngel di mar\u00eda</td>\n",
        "      <td> 15.0</td>\n",
        "      <td> 13</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> 10.17</td>\n",
        "      <td> 132.23</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester united</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "0   sergio ag\u00fcero   19.2     16     14        3               34   \n",
        "1     eden hazard   18.9     21      8        4               17   \n",
        "2  alexis s\u00e1nchez   17.6    NaN     12        7               29   \n",
        "3      yaya tour\u00e9   16.6     18      7        1               19   \n",
        "4  \u00e1ngel di mar\u00eda   15.0     13      3      NaN               13   \n",
        "\n",
        "   points_per_game  points  position               team  \n",
        "0            13.12  209.98   forward    manchester city  \n",
        "1            13.05  274.04  midfield            chelsea  \n",
        "2            11.19  223.86   forward            arsenal  \n",
        "3            10.99  197.91  midfield    manchester city  \n",
        "4            10.17  132.23  midfield  manchester united  "
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Missing Values aka NaNs"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Counting Rows with NaNs"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nans = df.shape[0] - df.dropna().shape[0]\n",
      "\n",
      "print('%d rows have missing values' % nans)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "3 rows have missing values\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Selecting NaN Rows"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Selecting all rows that have NaNs in the `assists` column\n",
      "\n",
      "df[df['assists'].isnull()]"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>   \u00e1ngel di mar\u00eda</td>\n",
        "      <td> 15.0</td>\n",
        "      <td> 13</td>\n",
        "      <td> 3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> 10.17</td>\n",
        "      <td> 132.23</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester united</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> santiago cazorla</td>\n",
        "      <td> 14.8</td>\n",
        "      <td> 20</td>\n",
        "      <td> 4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td>  9.97</td>\n",
        "      <td>    NaN</td>\n",
        "      <td> midfield</td>\n",
        "      <td>           arsenal</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "             player salary  games  goals  assists  shots_on_target  \\\n",
        "4    \u00e1ngel di mar\u00eda   15.0     13      3      NaN               13   \n",
        "5  santiago cazorla   14.8     20      4      NaN               20   \n",
        "\n",
        "   points_per_game  points  position               team  \n",
        "4            10.17  132.23  midfield  manchester united  \n",
        "5             9.97     NaN  midfield            arsenal  "
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Selecting non-NaN Rows"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[df['assists'].notnull()]"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td> 19.2</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td>  3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td>  forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td>  4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "      <td> midfield</td>\n",
        "      <td>         chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td> 17.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 12</td>\n",
        "      <td>  7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td>  forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>     yaya tour\u00e9</td>\n",
        "      <td> 16.6</td>\n",
        "      <td> 18</td>\n",
        "      <td>  7</td>\n",
        "      <td>  1</td>\n",
        "      <td> 19</td>\n",
        "      <td> 10.99</td>\n",
        "      <td> 197.91</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>    david silva</td>\n",
        "      <td> 14.3</td>\n",
        "      <td> 15</td>\n",
        "      <td>  6</td>\n",
        "      <td>  2</td>\n",
        "      <td> 11</td>\n",
        "      <td> 10.35</td>\n",
        "      <td> 155.26</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>  cesc f\u00e0bregas</td>\n",
        "      <td> 14.0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "      <td> midfield</td>\n",
        "      <td>         chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> steven gerrard</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td>  5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "      <td> midfield</td>\n",
        "      <td>       liverpool</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "0   sergio ag\u00fcero   19.2     16     14        3               34   \n",
        "1     eden hazard   18.9     21      8        4               17   \n",
        "2  alexis s\u00e1nchez   17.6    NaN     12        7               29   \n",
        "3      yaya tour\u00e9   16.6     18      7        1               19   \n",
        "6     david silva   14.3     15      6        2               11   \n",
        "7   cesc f\u00e0bregas   14.0     20      2       14               10   \n",
        "8  saido berahino   13.8     21      9        0               20   \n",
        "9  steven gerrard   13.8     20      5        1               11   \n",
        "\n",
        "   points_per_game  points  position             team  \n",
        "0            13.12  209.98   forward  manchester city  \n",
        "1            13.05  274.04  midfield          chelsea  \n",
        "2            11.19  223.86   forward          arsenal  \n",
        "3            10.99  197.91  midfield  manchester city  \n",
        "6            10.35  155.26  midfield  manchester city  \n",
        "7            10.47  209.49  midfield          chelsea  \n",
        "8             7.02  147.43   forward        west brom  \n",
        "9             7.50  150.01  midfield        liverpool  "
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Filling NaN Rows"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Filling NaN cells with default value 0\n",
      "\n",
      "df.fillna(value=0, inplace=True)\n",
      "df"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>    sergio ag\u00fcero</td>\n",
        "      <td> 19.2</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td>  3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td>  forward</td>\n",
        "      <td>   manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>      eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td>  4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "      <td> midfield</td>\n",
        "      <td>           chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>   alexis s\u00e1nchez</td>\n",
        "      <td> 17.6</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td>  7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td>  forward</td>\n",
        "      <td>           arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>       yaya tour\u00e9</td>\n",
        "      <td> 16.6</td>\n",
        "      <td> 18</td>\n",
        "      <td>  7</td>\n",
        "      <td>  1</td>\n",
        "      <td> 19</td>\n",
        "      <td> 10.99</td>\n",
        "      <td> 197.91</td>\n",
        "      <td> midfield</td>\n",
        "      <td>   manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>   \u00e1ngel di mar\u00eda</td>\n",
        "      <td> 15.0</td>\n",
        "      <td> 13</td>\n",
        "      <td>  3</td>\n",
        "      <td>  0</td>\n",
        "      <td> 13</td>\n",
        "      <td> 10.17</td>\n",
        "      <td> 132.23</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester united</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> santiago cazorla</td>\n",
        "      <td> 14.8</td>\n",
        "      <td> 20</td>\n",
        "      <td>  4</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  9.97</td>\n",
        "      <td>   0.00</td>\n",
        "      <td> midfield</td>\n",
        "      <td>           arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>      david silva</td>\n",
        "      <td> 14.3</td>\n",
        "      <td> 15</td>\n",
        "      <td>  6</td>\n",
        "      <td>  2</td>\n",
        "      <td> 11</td>\n",
        "      <td> 10.35</td>\n",
        "      <td> 155.26</td>\n",
        "      <td> midfield</td>\n",
        "      <td>   manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>    cesc f\u00e0bregas</td>\n",
        "      <td> 14.0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "      <td> midfield</td>\n",
        "      <td>           chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>   saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  forward</td>\n",
        "      <td>         west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>   steven gerrard</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td>  5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td>  7.50</td>\n",
        "      <td> 150.01</td>\n",
        "      <td> midfield</td>\n",
        "      <td>         liverpool</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "             player salary  games  goals  assists  shots_on_target  \\\n",
        "0     sergio ag\u00fcero   19.2     16     14        3               34   \n",
        "1       eden hazard   18.9     21      8        4               17   \n",
        "2    alexis s\u00e1nchez   17.6      0     12        7               29   \n",
        "3        yaya tour\u00e9   16.6     18      7        1               19   \n",
        "4    \u00e1ngel di mar\u00eda   15.0     13      3        0               13   \n",
        "5  santiago cazorla   14.8     20      4        0               20   \n",
        "6       david silva   14.3     15      6        2               11   \n",
        "7     cesc f\u00e0bregas   14.0     20      2       14               10   \n",
        "8    saido berahino   13.8     21      9        0               20   \n",
        "9    steven gerrard   13.8     20      5        1               11   \n",
        "\n",
        "   points_per_game  points  position               team  \n",
        "0            13.12  209.98   forward    manchester city  \n",
        "1            13.05  274.04  midfield            chelsea  \n",
        "2            11.19  223.86   forward            arsenal  \n",
        "3            10.99  197.91  midfield    manchester city  \n",
        "4            10.17  132.23  midfield  manchester united  \n",
        "5             9.97    0.00  midfield            arsenal  \n",
        "6            10.35  155.26  midfield    manchester city  \n",
        "7            10.47  209.49  midfield            chelsea  \n",
        "8             7.02  147.43   forward          west brom  \n",
        "9             7.50  150.01  midfield          liverpool  "
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Appending Rows to a DataFrame"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Adding an \"empty\" row to the DataFrame\n",
      "\n",
      "import numpy as np\n",
      "\n",
      "df = df.append(pd.Series(\n",
      "                [np.nan]*len(df.columns), # Fill cells with NaNs\n",
      "                index=df.columns),    \n",
      "                ignore_index=True)\n",
      "\n",
      "df.tail(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>8 </th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td> 7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  forward</td>\n",
        "      <td> west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9 </th>\n",
        "      <td> steven gerrard</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td>  5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td> 7.50</td>\n",
        "      <td> 150.01</td>\n",
        "      <td> midfield</td>\n",
        "      <td> liverpool</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>      NaN</td>\n",
        "      <td>       NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "            player salary  games  goals  assists  shots_on_target  \\\n",
        "8   saido berahino   13.8     21      9        0               20   \n",
        "9   steven gerrard   13.8     20      5        1               11   \n",
        "10             NaN    NaN    NaN    NaN      NaN              NaN   \n",
        "\n",
        "    points_per_game  points  position       team  \n",
        "8              7.02  147.43   forward  west brom  \n",
        "9              7.50  150.01  midfield  liverpool  \n",
        "10              NaN     NaN       NaN        NaN  "
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Filling cells with data\n",
      "\n",
      "df.loc[df.index[-1], 'player'] = 'new player'\n",
      "df.loc[df.index[-1], 'salary'] = 12.3\n",
      "df.tail(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>8 </th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td> 7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  forward</td>\n",
        "      <td> west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9 </th>\n",
        "      <td> steven gerrard</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 20</td>\n",
        "      <td>  5</td>\n",
        "      <td>  1</td>\n",
        "      <td> 11</td>\n",
        "      <td> 7.50</td>\n",
        "      <td> 150.01</td>\n",
        "      <td> midfield</td>\n",
        "      <td> liverpool</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>     new player</td>\n",
        "      <td> 12.3</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",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "            player salary  games  goals  assists  shots_on_target  \\\n",
        "8   saido berahino   13.8     21      9        0               20   \n",
        "9   steven gerrard   13.8     20      5        1               11   \n",
        "10      new player   12.3    NaN    NaN      NaN              NaN   \n",
        "\n",
        "    points_per_game  points  position       team  \n",
        "8              7.02  147.43   forward  west brom  \n",
        "9              7.50  150.01  midfield  liverpool  \n",
        "10              NaN     NaN       NaN        NaN  "
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Sorting and Reindexing DataFrames"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Sorting the DataFrame by a certain column (from highest to lowest)\n",
      "\n",
      "df.sort('goals', ascending=False, inplace=True)\n",
      "df.head()"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td> 19.2</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td>  forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td> 17.6</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td>  forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td> 0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td> 4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "      <td> midfield</td>\n",
        "      <td>         chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>     yaya tour\u00e9</td>\n",
        "      <td> 16.6</td>\n",
        "      <td> 18</td>\n",
        "      <td>  7</td>\n",
        "      <td> 1</td>\n",
        "      <td> 19</td>\n",
        "      <td> 10.99</td>\n",
        "      <td> 197.91</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "0   sergio ag\u00fcero   19.2     16     14        3               34   \n",
        "2  alexis s\u00e1nchez   17.6      0     12        7               29   \n",
        "8  saido berahino   13.8     21      9        0               20   \n",
        "1     eden hazard   18.9     21      8        4               17   \n",
        "3      yaya tour\u00e9   16.6     18      7        1               19   \n",
        "\n",
        "   points_per_game  points  position             team  \n",
        "0            13.12  209.98   forward  manchester city  \n",
        "2            11.19  223.86   forward          arsenal  \n",
        "8             7.02  147.43   forward        west brom  \n",
        "1            13.05  274.04  midfield          chelsea  \n",
        "3            10.99  197.91  midfield  manchester city  "
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Optional reindexing of the DataFrame after sorting\n",
      "\n",
      "df.index = range(1,len(df.index)+1)\n",
      "df.head()"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td> 19.2</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td>  forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td> 17.6</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td>  forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td> 0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td>  forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>    eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td> 4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "      <td> midfield</td>\n",
        "      <td>         chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>     yaya tour\u00e9</td>\n",
        "      <td> 16.6</td>\n",
        "      <td> 18</td>\n",
        "      <td>  7</td>\n",
        "      <td> 1</td>\n",
        "      <td> 19</td>\n",
        "      <td> 10.99</td>\n",
        "      <td> 197.91</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "1   sergio ag\u00fcero   19.2     16     14        3               34   \n",
        "2  alexis s\u00e1nchez   17.6      0     12        7               29   \n",
        "3  saido berahino   13.8     21      9        0               20   \n",
        "4     eden hazard   18.9     21      8        4               17   \n",
        "5      yaya tour\u00e9   16.6     18      7        1               19   \n",
        "\n",
        "   points_per_game  points  position             team  \n",
        "1            13.12  209.98   forward  manchester city  \n",
        "2            11.19  223.86   forward          arsenal  \n",
        "3             7.02  147.43   forward        west brom  \n",
        "4            13.05  274.04  midfield          chelsea  \n",
        "5            10.99  197.91  midfield  manchester city  "
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Updating Columns"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Creating a dummy DataFrame with changes in the `salary` column\n",
      "\n",
      "df_2 = df.copy()\n",
      "df_2.loc[0:2, 'salary'] = [20.0, 15.0]\n",
      "df_2.head(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td>   20</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td> forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td>   15</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td> forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td> 0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td> forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "1   sergio ag\u00fcero     20     16     14        3               34   \n",
        "2  alexis s\u00e1nchez     15      0     12        7               29   \n",
        "3  saido berahino   13.8     21      9        0               20   \n",
        "\n",
        "   points_per_game  points position             team  \n",
        "1            13.12  209.98  forward  manchester city  \n",
        "2            11.19  223.86  forward          arsenal  \n",
        "3             7.02  147.43  forward        west brom  "
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Temporarily use the `player` columns as indices to \n",
      "# apply the update functions\n",
      "\n",
      "df.set_index('player', inplace=True)\n",
      "df_2.set_index('player', inplace=True)\n",
      "df.head(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>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>player</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>sergio ag\u00fcero</th>\n",
        "      <td> 19.2</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td> forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>alexis s\u00e1nchez</th>\n",
        "      <td> 17.6</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td> forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>saido berahino</th>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td> 0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td> forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "               salary  games  goals  assists  shots_on_target  \\\n",
        "player                                                          \n",
        "sergio ag\u00fcero    19.2     16     14        3               34   \n",
        "alexis s\u00e1nchez   17.6      0     12        7               29   \n",
        "saido berahino   13.8     21      9        0               20   \n",
        "\n",
        "                points_per_game  points position             team  \n",
        "player                                                             \n",
        "sergio ag\u00fcero             13.12  209.98  forward  manchester city  \n",
        "alexis s\u00e1nchez            11.19  223.86  forward          arsenal  \n",
        "saido berahino             7.02  147.43  forward        west brom  "
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Update the `salary` column\n",
      "df.update(other=df_2['salary'], overwrite=True)\n",
      "df.head(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>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>player</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>sergio ag\u00fcero</th>\n",
        "      <td>   20</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td> forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>alexis s\u00e1nchez</th>\n",
        "      <td>   15</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td> forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>saido berahino</th>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td> 0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td> forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "               salary  games  goals  assists  shots_on_target  \\\n",
        "player                                                          \n",
        "sergio ag\u00fcero      20     16     14        3               34   \n",
        "alexis s\u00e1nchez     15      0     12        7               29   \n",
        "saido berahino   13.8     21      9        0               20   \n",
        "\n",
        "                points_per_game  points position             team  \n",
        "player                                                             \n",
        "sergio ag\u00fcero             13.12  209.98  forward  manchester city  \n",
        "alexis s\u00e1nchez            11.19  223.86  forward          arsenal  \n",
        "saido berahino             7.02  147.43  forward        west brom  "
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Reset the indices\n",
      "df.reset_index(inplace=True)\n",
      "df.head(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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td>   20</td>\n",
        "      <td> 16</td>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 34</td>\n",
        "      <td> 13.12</td>\n",
        "      <td> 209.98</td>\n",
        "      <td> forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td>   15</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td> forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td> 21</td>\n",
        "      <td>  9</td>\n",
        "      <td> 0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  7.02</td>\n",
        "      <td> 147.43</td>\n",
        "      <td> forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "0   sergio ag\u00fcero     20     16     14        3               34   \n",
        "1  alexis s\u00e1nchez     15      0     12        7               29   \n",
        "2  saido berahino   13.8     21      9        0               20   \n",
        "\n",
        "   points_per_game  points position             team  \n",
        "0            13.12  209.98  forward  manchester city  \n",
        "1            11.19  223.86  forward          arsenal  \n",
        "2             7.02  147.43  forward        west brom  "
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Chaining Conditions - Using Bitwise Operators"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Selecting only those players that either playing for Arsenal or Chelsea\n",
      "\n",
      "df[ (df['team'] == 'arsenal') | (df['team'] == 'chelsea') ]"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>   alexis s\u00e1nchez</td>\n",
        "      <td>   15</td>\n",
        "      <td>  0</td>\n",
        "      <td> 12</td>\n",
        "      <td>  7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td>  forward</td>\n",
        "      <td> arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>      eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> 21</td>\n",
        "      <td>  8</td>\n",
        "      <td>  4</td>\n",
        "      <td> 17</td>\n",
        "      <td> 13.05</td>\n",
        "      <td> 274.04</td>\n",
        "      <td> midfield</td>\n",
        "      <td> chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td> santiago cazorla</td>\n",
        "      <td> 14.8</td>\n",
        "      <td> 20</td>\n",
        "      <td>  4</td>\n",
        "      <td>  0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  9.97</td>\n",
        "      <td>   0.00</td>\n",
        "      <td> midfield</td>\n",
        "      <td> arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>    cesc f\u00e0bregas</td>\n",
        "      <td> 14.0</td>\n",
        "      <td> 20</td>\n",
        "      <td>  2</td>\n",
        "      <td> 14</td>\n",
        "      <td> 10</td>\n",
        "      <td> 10.47</td>\n",
        "      <td> 209.49</td>\n",
        "      <td> midfield</td>\n",
        "      <td> chelsea</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "             player salary  games  goals  assists  shots_on_target  \\\n",
        "1    alexis s\u00e1nchez     15      0     12        7               29   \n",
        "3       eden hazard   18.9     21      8        4               17   \n",
        "7  santiago cazorla   14.8     20      4        0               20   \n",
        "9     cesc f\u00e0bregas   14.0     20      2       14               10   \n",
        "\n",
        "   points_per_game  points  position     team  \n",
        "1            11.19  223.86   forward  arsenal  \n",
        "3            13.05  274.04  midfield  chelsea  \n",
        "7             9.97    0.00  midfield  arsenal  \n",
        "9            10.47  209.49  midfield  chelsea  "
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Selecting forwards from Arsenal only\n",
      "\n",
      "df[ (df['team'] == 'arsenal') & (df['position'] == 'forward') ]"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>games</th>\n",
        "      <th>goals</th>\n",
        "      <th>assists</th>\n",
        "      <th>shots_on_target</th>\n",
        "      <th>points_per_game</th>\n",
        "      <th>points</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td> 15</td>\n",
        "      <td> 0</td>\n",
        "      <td> 12</td>\n",
        "      <td> 7</td>\n",
        "      <td> 29</td>\n",
        "      <td> 11.19</td>\n",
        "      <td> 223.86</td>\n",
        "      <td> forward</td>\n",
        "      <td> arsenal</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "           player salary  games  goals  assists  shots_on_target  \\\n",
        "1  alexis s\u00e1nchez     15      0     12        7               29   \n",
        "\n",
        "   points_per_game  points position     team  \n",
        "1            11.19  223.86  forward  arsenal  "
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Column Types"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[[back to section overview](#Sections)]"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Printing Column Types"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "types = df.columns.to_series().groupby(df.dtypes).groups\n",
      "types"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "{dtype('float64'): ['games',\n",
        "  'goals',\n",
        "  'assists',\n",
        "  'shots_on_target',\n",
        "  'points_per_game',\n",
        "  'points'],\n",
        " dtype('O'): ['player', 'salary', 'position', 'team']}"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Selecting by Column Type"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# select string columns\n",
      "df.loc[:, (df.dtypes == np.dtype('O')).values].head()"
     ],
     "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>player</th>\n",
        "      <th>salary</th>\n",
        "      <th>position</th>\n",
        "      <th>team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  sergio ag\u00fcero</td>\n",
        "      <td>   20</td>\n",
        "      <td>  forward</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> alexis s\u00e1nchez</td>\n",
        "      <td>   15</td>\n",
        "      <td>  forward</td>\n",
        "      <td>         arsenal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> saido berahino</td>\n",
        "      <td> 13.8</td>\n",
        "      <td>  forward</td>\n",
        "      <td>       west brom</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>    eden hazard</td>\n",
        "      <td> 18.9</td>\n",
        "      <td> midfield</td>\n",
        "      <td>         chelsea</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>     yaya tour\u00e9</td>\n",
        "      <td> 16.6</td>\n",
        "      <td> midfield</td>\n",
        "      <td> manchester city</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "           player salary  position             team\n",
        "0   sergio ag\u00fcero     20   forward  manchester city\n",
        "1  alexis s\u00e1nchez     15   forward          arsenal\n",
        "2  saido berahino   13.8   forward        west brom\n",
        "3     eden hazard   18.9  midfield          chelsea\n",
        "4      yaya tour\u00e9   16.6  midfield  manchester city"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<br>\n",
      "<br>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Converting Column Types"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['salary'] = df['salary'].astype(float)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "types = df.columns.to_series().groupby(df.dtypes).groups\n",
      "types"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "{dtype('float64'): ['salary',\n",
        "  'games',\n",
        "  'goals',\n",
        "  'assists',\n",
        "  'shots_on_target',\n",
        "  'points_per_game',\n",
        "  'points'],\n",
        " dtype('O'): ['player', 'position', 'team']}"
       ]
      }
     ],
     "prompt_number": 26
    }
   ],
   "metadata": {}
  }
 ]
}