pandas_time_series_basics.ipynb

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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Pandas Time Series Basics\n",
      "\n",
      "- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n",
      "- **Date:** -\n",
      "- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n",
      "- **Note:**"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Import modules"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from datetime import datetime\n",
      "import pandas as pd\n",
      "%matplotlib inline\n",
      "import matplotlib.pyplot as pyplot"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 113
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Create a dataframe"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = {'date': ['2014-05-01 18:47:05.069722', '2014-05-01 18:47:05.119994', '2014-05-02 18:47:05.178768', '2014-05-02 18:47:05.230071', '2014-05-02 18:47:05.230071', '2014-05-02 18:47:05.280592', '2014-05-03 18:47:05.332662', '2014-05-03 18:47:05.385109', '2014-05-04 18:47:05.436523', '2014-05-04 18:47:05.486877'], \n",
      "        'battle_deaths': [34, 25, 26, 15, 15, 14, 26, 25, 62, 41]}\n",
      "df = pd.DataFrame(data, columns = ['date', 'battle_deaths'])\n",
      "print(df)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                         date  battle_deaths\n",
        "0  2014-05-01 18:47:05.069722             34\n",
        "1  2014-05-01 18:47:05.119994             25\n",
        "2  2014-05-02 18:47:05.178768             26\n",
        "3  2014-05-02 18:47:05.230071             15\n",
        "4  2014-05-02 18:47:05.230071             15\n",
        "5  2014-05-02 18:47:05.280592             14\n",
        "6  2014-05-03 18:47:05.332662             26\n",
        "7  2014-05-03 18:47:05.385109             25\n",
        "8  2014-05-04 18:47:05.436523             62\n",
        "9  2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[10 rows x 2 columns]\n"
       ]
      }
     ],
     "prompt_number": 114
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Convert df['date'] from string to datetime"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['date'] = pd.to_datetime(df['date'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 115
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Set df['date'] as the index and delete the column"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.index = df['date']\n",
      "del df['date']\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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.069722</th>\n",
        "      <td> 34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.119994</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.178768</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.280592</th>\n",
        "      <td> 14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 41</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>10 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 116,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-01 18:47:05.069722             34\n",
        "2014-05-01 18:47:05.119994             25\n",
        "2014-05-02 18:47:05.178768             26\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.280592             14\n",
        "2014-05-03 18:47:05.332662             26\n",
        "2014-05-03 18:47:05.385109             25\n",
        "2014-05-04 18:47:05.436523             62\n",
        "2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[10 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 116
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### View all observations that occured in 2014"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['2014']"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.069722</th>\n",
        "      <td> 34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.119994</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.178768</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.280592</th>\n",
        "      <td> 14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 41</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>10 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 117,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-01 18:47:05.069722             34\n",
        "2014-05-01 18:47:05.119994             25\n",
        "2014-05-02 18:47:05.178768             26\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.280592             14\n",
        "2014-05-03 18:47:05.332662             26\n",
        "2014-05-03 18:47:05.385109             25\n",
        "2014-05-04 18:47:05.436523             62\n",
        "2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[10 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 117
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### View all observations that occured in May 2014"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['2014-05']"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.069722</th>\n",
        "      <td> 34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.119994</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.178768</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.280592</th>\n",
        "      <td> 14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 41</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>10 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 118,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-01 18:47:05.069722             34\n",
        "2014-05-01 18:47:05.119994             25\n",
        "2014-05-02 18:47:05.178768             26\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.280592             14\n",
        "2014-05-03 18:47:05.332662             26\n",
        "2014-05-03 18:47:05.385109             25\n",
        "2014-05-04 18:47:05.436523             62\n",
        "2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[10 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 118
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Observations after May 3rd, 2014"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[datetime(2014, 5, 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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 41</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>4 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 119,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-03 18:47:05.332662             26\n",
        "2014-05-03 18:47:05.385109             25\n",
        "2014-05-04 18:47:05.436523             62\n",
        "2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[4 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 119
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Observations between May 3rd and May 4th"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['5/3/2014':'5/4/2014']"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 41</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>4 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 120,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-03 18:47:05.332662             26\n",
        "2014-05-03 18:47:05.385109             25\n",
        "2014-05-04 18:47:05.436523             62\n",
        "2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[4 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 120
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Truncation observations after May 2nd 2014"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.truncate(after='5/3/2014')"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.069722</th>\n",
        "      <td> 34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.119994</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.178768</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.280592</th>\n",
        "      <td> 14</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>6 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 121,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-01 18:47:05.069722             34\n",
        "2014-05-01 18:47:05.119994             25\n",
        "2014-05-02 18:47:05.178768             26\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.280592             14\n",
        "\n",
        "[6 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 121
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Observations of May 2014"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix['5-2014']"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.069722</th>\n",
        "      <td> 34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.119994</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.178768</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.280592</th>\n",
        "      <td> 14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 41</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>10 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 122,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-01 18:47:05.069722             34\n",
        "2014-05-01 18:47:05.119994             25\n",
        "2014-05-02 18:47:05.178768             26\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.230071             15\n",
        "2014-05-02 18:47:05.280592             14\n",
        "2014-05-03 18:47:05.332662             26\n",
        "2014-05-03 18:47:05.385109             25\n",
        "2014-05-04 18:47:05.436523             62\n",
        "2014-05-04 18:47:05.486877             41\n",
        "\n",
        "[10 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 122
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Count the number of observations per timestamp"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.groupby(level=0).count()"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.069722</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-01 18:47:05.119994</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.178768</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.230071</th>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02 18:47:05.280592</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.332662</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03 18:47:05.385109</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.436523</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 18:47:05.486877</th>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>9 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 123,
       "text": [
        "                            battle_deaths\n",
        "date                                     \n",
        "2014-05-01 18:47:05.069722              1\n",
        "2014-05-01 18:47:05.119994              1\n",
        "2014-05-02 18:47:05.178768              1\n",
        "2014-05-02 18:47:05.230071              2\n",
        "2014-05-02 18:47:05.280592              1\n",
        "2014-05-03 18:47:05.332662              1\n",
        "2014-05-03 18:47:05.385109              1\n",
        "2014-05-04 18:47:05.436523              1\n",
        "2014-05-04 18:47:05.486877              1\n",
        "\n",
        "[9 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 123
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Mean value of battle_deaths per day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.resample('D', how='mean')"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01</th>\n",
        "      <td> 29.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02</th>\n",
        "      <td> 17.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03</th>\n",
        "      <td> 25.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04</th>\n",
        "      <td> 51.5</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>4 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 124,
       "text": [
        "            battle_deaths\n",
        "date                     \n",
        "2014-05-01           29.5\n",
        "2014-05-02           17.5\n",
        "2014-05-03           25.5\n",
        "2014-05-04           51.5\n",
        "\n",
        "[4 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 124
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Total value of battle_deaths per day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.resample('D', how='sum')"
     ],
     "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>battle_deaths</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-01</th>\n",
        "      <td>  59</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-02</th>\n",
        "      <td>  70</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-03</th>\n",
        "      <td>  51</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04</th>\n",
        "      <td> 103</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>4 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 125,
       "text": [
        "            battle_deaths\n",
        "date                     \n",
        "2014-05-01             59\n",
        "2014-05-02             70\n",
        "2014-05-03             51\n",
        "2014-05-04            103\n",
        "\n",
        "[4 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 125
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Plot of the total battle deaths per day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.resample('D', how='sum').plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 128,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10809de50>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x108052d90>"
       ]
      }
     ],
     "prompt_number": 128
    }
   ],
   "metadata": {}
  }
 ]
}