Pandas, Bar Chart Annotations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>person</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAA</td>\n",
       "      <td>-0.964270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BBB</td>\n",
       "      <td>1.312816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CCC</td>\n",
       "      <td>-0.588045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DDD</td>\n",
       "      <td>0.510745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EEE</td>\n",
       "      <td>1.767899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>FFF</td>\n",
       "      <td>0.544674</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  person     score\n",
       "0    AAA -0.964270\n",
       "1    BBB  1.312816\n",
       "2    CCC -0.588045\n",
       "3    DDD  0.510745\n",
       "4    EEE  1.767899\n",
       "5    FFF  0.544674"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({'score':np.random.randn(6),\n",
    "                   'person':[x*3 for x in list('ABCDEF')]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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CnA9GLLfGPxK9vv8sfkYx0YzlgxHbHbbq1BTbSyW9RNJmSYsj4stN9UfYvl3S7pKGJH0s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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x351ef29208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.set_index(['person']).plot(kind='barh')\n",
    "ax.invert_yaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def autolabel(rects):\n",
    "    #if height constant: hbars, vbars otherwise\n",
    "    if (np.diff([plt.getp(item, 'width') for item in rects])==0).all():\n",
    "        x_pos = [rect.get_x() + rect.get_width()/2. for rect in rects]\n",
    "        y_pos = [rect.get_y() + 1.05*rect.get_height() for rect in rects]\n",
    "        scores = [plt.getp(item, 'height') for item in rects]\n",
    "    else:\n",
    "        x_pos = [rect.get_width()+.3 for rect in rects]\n",
    "        y_pos = [rect.get_y()+.3*rect.get_height() for rect in rects]\n",
    "        scores = [plt.getp(item, 'width') for item in rects]\n",
    "    # attach some text labels\n",
    "    for rect, x, y, s in zip(rects, x_pos, y_pos, scores):\n",
    "        ax.text(x, \n",
    "                y,\n",
    "                '%s'%s,\n",
    "                ha='center', va='bottom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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jr68vW7duLbY/eiyUiIiICPk3Nl63bp295m/48OH4+vraF4YUVqNGjSIPP09JSbHXB4Lz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x351fd54be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.set_index(['person']).plot(kind='bar', figsize=(10,7), \n",
    "              color=['dodgerblue', 'slategray'], fontsize=13)\n",
    "\n",
    "ax.set_alpha(0.8)\n",
    "ax.set_title(\"Bar\")#,fontsize=18)\n",
    "autolabel(ax.patches)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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C59zVpZRPA0r+fOuX+sByG5SIyCk0ceJEOnfuTEFBAQMHDqRZs2a88MILmBmDBw/mzTff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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x351fad20b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.set_index(['person']).plot(kind='barh', figsize=(10,7), \n",
    "              color=['dodgerblue', 'slategray'], fontsize=13)\n",
    "\n",
    "ax.set_alpha(0.8)\n",
    "ax.set_title(\"BarH\")#,fontsize=18)\n",
    "autolabel(ax.patches)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}