cobbler plots?

cobbler.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pandas\n",
    "import seaborn\n",
    "\n",
    "seaborn.set(style='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Class      Season\n",
       "Treated    SuFa      175\n",
       "           Wi         40\n",
       "           Sp        120\n",
       "Untreated  SuFa      200\n",
       "           Wi         50\n",
       "           Sp        251\n",
       "Name: Volume, dtype: int64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes = ('Treated', 'Untreated')\n",
    "seasons = ('SuFa', 'Wi', 'Sp')\n",
    "index = pandas.MultiIndex.from_product([classes, seasons], names=['Class', 'Season'])\n",
    "values = [175, 40, 120, 200, 50, 251]\n",
    "dataframe = pandas.DataFrame(data=values, index=index, columns=['Volume'])\n",
    "\n",
    "data = dataframe['Volume']\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x8bad668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4, 4))\n",
    "ax.set_aspect('equal')\n",
    "\n",
    "xgroup = 'Class'\n",
    "ygroup = 'Season'\n",
    "\n",
    "groups = data.groupby(level=xgroup)\n",
    "\n",
    "colors = {\n",
    "    'Treated': seaborn.color_palette(palette='deep')[0],\n",
    "    'Untreated': seaborn.color_palette(palette='deep')[1]\n",
    "}\n",
    "\n",
    "xstart = 0\n",
    "xticks = []\n",
    "xticklabels = []\n",
    "for name, group in groups:\n",
    "    color = colors[name]\n",
    "    xstop = group.sum() / data.sum() + xstart\n",
    "    width = xstop - xstart\n",
    "    xcenter = xstart + 0.5 * width\n",
    "    \n",
    "    xticks.append(xcenter)\n",
    "    xticklabels.append(name)\n",
    "    \n",
    "    yvals = group / group.sum()\n",
    "    ystart = 0\n",
    "    for height in yvals:\n",
    "        ystop = ystart + height\n",
    "        ycenter = ystart + 0.5 * height\n",
    "        rect = plt.Rectangle((xstart, 0), width, ystop, alpha=0.2, facecolor=color, linewidth=0)\n",
    "        ax.add_patch(rect)\n",
    "        ax.annotate('{:.0f}%'.format(100*height), (xcenter, ycenter), (0, 0), \n",
    "                    xycoords='data', textcoords='offset points',\n",
    "                    ha='center', va='center')\n",
    "        \n",
    "        ystart = ystop\n",
    "    \n",
    "    xstart = xstop\n",
    "\n",
    "\n",
    "ax.set_xticks(xticks)\n",
    "ax.set_xticklabels(xticklabels)\n",
    "ax.set_yticks([])\n",
    "seaborn.despine(left=True, bottom=True)"
   ]
  }
 ],
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