bar-chart.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:31256c1bafd6e0b4a9bec7e0f7b6ca731776eefaa740ebfa36bfa7e48da59e7c"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Libraries required"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We have data from 2008 on the number of complaints recevied by each PCT. We have the PCT name, code and the region it is located."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Import data from CSV\n",
      "pct = pd.read_csv('/vagrant/data/PCT-2008-clean.csv', header=0, index_col=1)\n",
      "pct"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Let's check the number of rows of data we have\n",
      "# This is the first element in the tuple returned from .shape\n",
      "pct.shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Let's check column names\n",
      "pct.columns.values"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Check that our numerical column is of type int\n",
      "print pct['Complaints'][107]\n",
      "type(pct['Complaints'][0])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Top 10 PCT By Complaints"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "top_10_complaints = pct[['Name', 'Complaints']].sort('Complaints', ascending=True)[-10:]\n",
      "top_10_complaints_name = top_10_complaints.set_index('Name')\n",
      "top_10_complaints_name"
     ],
     "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>Complaints</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Name</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Barking, Havering And Redbridge Hospitals NHS Trust</th>\n",
        "      <td>  940</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Nottingham University Hospitals NHS Trust</th>\n",
        "      <td>  986</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Imperial College Health Care Trust</th>\n",
        "      <td> 1006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Royal Free Hampstead NHS Trust</th>\n",
        "      <td> 1008</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Brighton And Sussex University Hospitals NHS Trust</th>\n",
        "      <td> 1030</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>East And North Hertfordshire NHS Trust</th>\n",
        "      <td> 1061</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Barts And The London NHS Trust</th>\n",
        "      <td> 1066</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Portsmouth Hospitals NHS Trust</th>\n",
        "      <td> 1119</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Leeds Teaching Hospitals NHS Trust</th>\n",
        "      <td> 1396</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>University Hospitals Of Leicester NHS Trust</th>\n",
        "      <td> 1426</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 171,
       "text": [
        "                                                     Complaints\n",
        "Name                                                           \n",
        "Barking, Havering And Redbridge Hospitals NHS Trust         940\n",
        "Nottingham University Hospitals NHS Trust                   986\n",
        "Imperial College Health Care Trust                         1006\n",
        "Royal Free Hampstead NHS Trust                             1008\n",
        "Brighton And Sussex University Hospitals NHS Trust         1030\n",
        "East And North Hertfordshire NHS Trust                     1061\n",
        "Barts And The London NHS Trust                             1066\n",
        "Portsmouth Hospitals NHS Trust                             1119\n",
        "Leeds Teaching Hospitals NHS Trust                         1396\n",
        "University Hospitals Of Leicester NHS Trust                1426"
       ]
      }
     ],
     "prompt_number": 171
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Make A Bar Chart"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline \n",
      "top_10_complaints_name.plot(kind='barh', color='red', edgecolor='red', grid=False, legend=False, figsize=(10,7), fontsize=12)\n",
      "plt.xlabel('Number of Complaints', fontsize=12)\n",
      "plt.ylabel('Primary Care Trust', fontsize=12)\n",
      "plt.tick_params(axis='y', which='both', left='off', right='off')    \n",
      "plt.tick_params(axis='x', which='both', top='off') "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAA6EAAAG0CAYAAADD3yErAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJar6/dyK+eAAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0xdb74050>"
       ]
      }
     ],
     "prompt_number": 172
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Let's get some documentation for plot\n",
      "help(top_10_complaints.plot)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}