ggplot_draw_line.ipynb

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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Draw a line 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": 4
    },
    {
     "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",
      "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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </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",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "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  \n",
        "0                41                14  \n",
        "1               214              1424  \n",
        "2               131               131  \n",
        "3                12                12  \n",
        "4               123                34  \n",
        "5               124               124  \n",
        "6               264              1124  \n",
        "7               311              1431  \n",
        "8               132               122  \n",
        "9               623              2563  "
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# scatterplot of attacker deaths vs defender deaths, with a line specified by slope and intercept\n",
      "ggplot(df, aes(x='deaths_attacker', y='deaths_defender')) + \\\n",
      "    geom_point() + \\\n",
      "    geom_abline(intercept=100, slope=0, colour=\"red\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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AABiHEgsAAADjUGIBAABgHEosAAAAjEOJBQAAgHEosQAAADAOJRYAAADGocQCAADAOJRY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\ndQixAAAAcB1CLAAAAFyHEAsAAADXeQOdOEfMerBGGwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10a8e8890>"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<ggplot: (279504957)>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    }
   ],
   "metadata": {}
  }
 ]
}