ggplot_line_plot.ipynb

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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Draw a line plot in ggplot\n",
      "\n",
      "This snippit was written by [Chris R. Albon](http://www.chrisralbon.com/) and is part of his collection of [well-documented Python snippits](https://github.com/chrisalbon/code_py). All code is written in Python 3 in iPython notebook and offered under the [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Import required modules\n",
      "from ggplot import *\n",
      "%matplotlib inline\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Create a dataset of battle data\n",
      "data = {'battle': ['Battle of Two Forks', 'Battle of Cochise', 'Battle of Bells', 'Battle of the Beach', 'Battle of Flatlander', 'Battle of Middorin', 'Battle of Massai', 'Battle of Monogrop', 'Battle of ', 'Battle of Sticks'], \n",
      "        'season': ['winter', 'fall', 'fall', 'fall', 'spring', 'winter', 'summer', 'winter', 'summer', 'summer'],\n",
      "        'terrain': ['mountains', 'mountains', 'mountains', 'beach', 'beach', 'plains', 'plains', 'city', 'city', 'city'],\n",
      "        'weather': ['rain', 'rain', 'cloudy', 'sunny', 'rain', 'rain', 'sunny', 'cloudy', 'rain', 'sunny'],\n",
      "        'victor': ['attacker', 'defender', 'attacker', 'defender', 'attacker', 'defender', 'attacker', 'defender', 'attacker', 'defender'],\n",
      "        'deaths_attacker': [425, 242, 323, 223, 783, 436, 324, 3321, 262, 843],\n",
      "        'deaths_defender': [423, 264, 1231, 23, 23, 42, 124, 631, 232, 213],\n",
      "        'wounded_attacker': [41, 214, 131, 12, 123, 124, 264, 311, 132, 623],\n",
      "        'wounded_defender': [14, 1424, 131, 12, 34, 124, 1124, 1431, 122, 2563],\n",
      "        'soldiers_attacker': [2532, 6346, 3341, 6732, 12563, 2356, 253, 5277, 2732, 6278],\n",
      "        'soldiers_defender': [37235, 2523, 2133, 1245, 2671, 7832, 2622, 3331, 2522, 26773],\n",
      "        'year': [1945, 1956, 1964, 1969, 1971, 1981, 1982, 1992, 1999, 2004]}\n",
      "df = pd.DataFrame(data)\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</th>\n",
        "      <th>deaths_attacker</th>\n",
        "      <th>deaths_defender</th>\n",
        "      <th>season</th>\n",
        "      <th>soldiers_attacker</th>\n",
        "      <th>soldiers_defender</th>\n",
        "      <th>terrain</th>\n",
        "      <th>victor</th>\n",
        "      <th>weather</th>\n",
        "      <th>wounded_attacker</th>\n",
        "      <th>wounded_defender</th>\n",
        "      <th>year</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  Battle of Two Forks</td>\n",
        "      <td>  425</td>\n",
        "      <td>  423</td>\n",
        "      <td> winter</td>\n",
        "      <td>  2532</td>\n",
        "      <td> 37235</td>\n",
        "      <td> mountains</td>\n",
        "      <td> attacker</td>\n",
        "      <td>   rain</td>\n",
        "      <td>  41</td>\n",
        "      <td>   14</td>\n",
        "      <td> 1945</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    Battle of Cochise</td>\n",
        "      <td>  242</td>\n",
        "      <td>  264</td>\n",
        "      <td>   fall</td>\n",
        "      <td>  6346</td>\n",
        "      <td>  2523</td>\n",
        "      <td> mountains</td>\n",
        "      <td> defender</td>\n",
        "      <td>   rain</td>\n",
        "      <td> 214</td>\n",
        "      <td> 1424</td>\n",
        "      <td> 1956</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>      Battle of Bells</td>\n",
        "      <td>  323</td>\n",
        "      <td> 1231</td>\n",
        "      <td>   fall</td>\n",
        "      <td>  3341</td>\n",
        "      <td>  2133</td>\n",
        "      <td> mountains</td>\n",
        "      <td> attacker</td>\n",
        "      <td> cloudy</td>\n",
        "      <td> 131</td>\n",
        "      <td>  131</td>\n",
        "      <td> 1964</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>  Battle of the Beach</td>\n",
        "      <td>  223</td>\n",
        "      <td>   23</td>\n",
        "      <td>   fall</td>\n",
        "      <td>  6732</td>\n",
        "      <td>  1245</td>\n",
        "      <td>     beach</td>\n",
        "      <td> defender</td>\n",
        "      <td>  sunny</td>\n",
        "      <td>  12</td>\n",
        "      <td>   12</td>\n",
        "      <td> 1969</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> Battle of Flatlander</td>\n",
        "      <td>  783</td>\n",
        "      <td>   23</td>\n",
        "      <td> spring</td>\n",
        "      <td> 12563</td>\n",
        "      <td>  2671</td>\n",
        "      <td>     beach</td>\n",
        "      <td> attacker</td>\n",
        "      <td>   rain</td>\n",
        "      <td> 123</td>\n",
        "      <td>   34</td>\n",
        "      <td> 1971</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>   Battle of Middorin</td>\n",
        "      <td>  436</td>\n",
        "      <td>   42</td>\n",
        "      <td> winter</td>\n",
        "      <td>  2356</td>\n",
        "      <td>  7832</td>\n",
        "      <td>    plains</td>\n",
        "      <td> defender</td>\n",
        "      <td>   rain</td>\n",
        "      <td> 124</td>\n",
        "      <td>  124</td>\n",
        "      <td> 1981</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>     Battle of Massai</td>\n",
        "      <td>  324</td>\n",
        "      <td>  124</td>\n",
        "      <td> summer</td>\n",
        "      <td>   253</td>\n",
        "      <td>  2622</td>\n",
        "      <td>    plains</td>\n",
        "      <td> attacker</td>\n",
        "      <td>  sunny</td>\n",
        "      <td> 264</td>\n",
        "      <td> 1124</td>\n",
        "      <td> 1982</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>   Battle of Monogrop</td>\n",
        "      <td> 3321</td>\n",
        "      <td>  631</td>\n",
        "      <td> winter</td>\n",
        "      <td>  5277</td>\n",
        "      <td>  3331</td>\n",
        "      <td>      city</td>\n",
        "      <td> defender</td>\n",
        "      <td> cloudy</td>\n",
        "      <td> 311</td>\n",
        "      <td> 1431</td>\n",
        "      <td> 1992</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>           Battle of </td>\n",
        "      <td>  262</td>\n",
        "      <td>  232</td>\n",
        "      <td> summer</td>\n",
        "      <td>  2732</td>\n",
        "      <td>  2522</td>\n",
        "      <td>      city</td>\n",
        "      <td> attacker</td>\n",
        "      <td>   rain</td>\n",
        "      <td> 132</td>\n",
        "      <td>  122</td>\n",
        "      <td> 1999</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>     Battle of Sticks</td>\n",
        "      <td>  843</td>\n",
        "      <td>  213</td>\n",
        "      <td> summer</td>\n",
        "      <td>  6278</td>\n",
        "      <td> 26773</td>\n",
        "      <td>      city</td>\n",
        "      <td> defender</td>\n",
        "      <td>  sunny</td>\n",
        "      <td> 623</td>\n",
        "      <td> 2563</td>\n",
        "      <td> 2004</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "                 battle  deaths_attacker  deaths_defender  season  \\\n",
        "0   Battle of Two Forks              425              423  winter   \n",
        "1     Battle of Cochise              242              264    fall   \n",
        "2       Battle of Bells              323             1231    fall   \n",
        "3   Battle of the Beach              223               23    fall   \n",
        "4  Battle of Flatlander              783               23  spring   \n",
        "5    Battle of Middorin              436               42  winter   \n",
        "6      Battle of Massai              324              124  summer   \n",
        "7    Battle of Monogrop             3321              631  winter   \n",
        "8            Battle of               262              232  summer   \n",
        "9      Battle of Sticks              843              213  summer   \n",
        "\n",
        "   soldiers_attacker  soldiers_defender    terrain    victor weather  \\\n",
        "0               2532              37235  mountains  attacker    rain   \n",
        "1               6346               2523  mountains  defender    rain   \n",
        "2               3341               2133  mountains  attacker  cloudy   \n",
        "3               6732               1245      beach  defender   sunny   \n",
        "4              12563               2671      beach  attacker    rain   \n",
        "5               2356               7832     plains  defender    rain   \n",
        "6                253               2622     plains  attacker   sunny   \n",
        "7               5277               3331       city  defender  cloudy   \n",
        "8               2732               2522       city  attacker    rain   \n",
        "9               6278              26773       city  defender   sunny   \n",
        "\n",
        "   wounded_attacker  wounded_defender  year  \n",
        "0                41                14  1945  \n",
        "1               214              1424  1956  \n",
        "2               131               131  1964  \n",
        "3                12                12  1969  \n",
        "4               123                34  1971  \n",
        "5               124               124  1981  \n",
        "6               264              1124  1982  \n",
        "7               311              1431  1992  \n",
        "8               132               122  1999  \n",
        "9               623              2563  2004  "
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Line plot of number of wounded soldiers per year\n",
      "ggplot(df, aes(x='year', y='wounded_defender')) + \\\n",
      "    geom_line()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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T4sWLVVlZqQMHDgTiLQAAAHQZK7D+EZAGNiYmRgMHDpQkhYeHKzExUbW1tdq/f78mTJgg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\nf3+NGTNGS5culd1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pGdjq6mq98MILevjhh/XCCy+oqqrKqFxAp9XW1mrjxo1dfmrWF21H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\n2MASERERkaT8F/aNBUA4A5Z0AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10a0df790>"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "<ggplot: (278978529)>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Drop non-numeric variables\n",
      "df = df.drop(['battle', 'season', 'terrain', 'victor', 'weather'], axis=1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Plot the value of each variable by year (note that the actual values won't make sense in this example)\n",
      "ggplot(pd.melt(df, id_vars=['year']), aes(x='year', y='value', color='variable')) + \\\n",
      "    geom_line()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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n3+euxWB0Gh83b0QkEmFfPkQQBPYlB/YlN631BWBvlqLnvmQyGYxEQ2iuqoFo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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10a04a490>"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<ggplot: (280215789)>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.to_csv('df.csv', encoding='utf-8')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    }
   ],
   "metadata": {}
  }
 ]
}