{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Baltimore City Salary Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import requests\n",
    "import StringIO as StringIO\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ipynb/.ipyvirt/local/lib/python2.7/site-packages/requests/packages/urllib3/util/ssl_.py:90: InsecurePlatformWarning: A true SSLContext object is not available. This prevents urllib3 from configuring SSL appropriately and may cause certain SSL connections to fail. For more information, see https://urllib3.readthedocs.org/en/latest/security.html#insecureplatformwarning.\n",
      "  InsecurePlatformWarning\n"
     ]
    }
   ],
   "source": [
    "url = \"https://data.baltimorecity.gov/api/views/2j28-xzd7/rows.csv?accessType=DOWNLOAD\"\n",
    "r = requests.get(url)\n",
    "data = StringIO.StringIO(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "read the urllib3 docs and decide if the warning matters to you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dataframe = pd.read_csv(data,header=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We read the CSV into a dataframe. The header is called out as row0. data is of type FILE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dataframe['AnnualSalary'] = dataframe['AnnualSalary'].str.lstrip('$')\n",
    "dataframe['AnnualSalary'] = dataframe['AnnualSalary'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/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>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>size</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobTitle</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>STATE'S ATTORNEY</th>\n",
       "      <td>  238772.0</td>\n",
       "      <td> 238772.000000</td>\n",
       "      <td>          NaN</td>\n",
       "      <td>   1</td>\n",
       "      <td> 238772</td>\n",
       "      <td> 238772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXECUTIVE LEVEL III</th>\n",
       "      <td> 1939968.0</td>\n",
       "      <td> 161664.000000</td>\n",
       "      <td> 23053.267708</td>\n",
       "      <td>  12</td>\n",
       "      <td> 132600</td>\n",
       "      <td> 200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CONTRACT SERV SPEC II</th>\n",
       "      <td> 6205482.0</td>\n",
       "      <td>  55905.243243</td>\n",
       "      <td> 28837.184910</td>\n",
       "      <td> 111</td>\n",
       "      <td>  15392</td>\n",
       "      <td> 187200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAYOR</th>\n",
       "      <td>  163365.0</td>\n",
       "      <td> 163365.000000</td>\n",
       "      <td>          NaN</td>\n",
       "      <td>   1</td>\n",
       "      <td> 163365</td>\n",
       "      <td> 163365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITY SOLICITOR</th>\n",
       "      <td>  163200.0</td>\n",
       "      <td> 163200.000000</td>\n",
       "      <td>          NaN</td>\n",
       "      <td>   1</td>\n",
       "      <td> 163200</td>\n",
       "      <td> 163200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIRECTOR PUBLIC WORKS</th>\n",
       "      <td>  163200.0</td>\n",
       "      <td> 163200.000000</td>\n",
       "      <td>          NaN</td>\n",
       "      <td>   1</td>\n",
       "      <td> 163200</td>\n",
       "      <td> 163200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CONTRACT SERVICES SPEC. I</th>\n",
       "      <td> 5366446.0</td>\n",
       "      <td>  44350.793388</td>\n",
       "      <td> 22709.853783</td>\n",
       "      <td> 121</td>\n",
       "      <td>  15392</td>\n",
       "      <td> 156000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITY AUDITOR</th>\n",
       "      <td>  153600.0</td>\n",
       "      <td> 153600.000000</td>\n",
       "      <td>          NaN</td>\n",
       "      <td>   1</td>\n",
       "      <td> 153600</td>\n",
       "      <td> 153600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXECUTIVE LEVEL II</th>\n",
       "      <td> 9653928.4</td>\n",
       "      <td> 116312.390361</td>\n",
       "      <td> 16394.384734</td>\n",
       "      <td>  83</td>\n",
       "      <td>  80000</td>\n",
       "      <td> 150756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POLICE COMMAND STAFF II</th>\n",
       "      <td> 1631204.0</td>\n",
       "      <td> 116514.571429</td>\n",
       "      <td> 12626.188424</td>\n",
       "      <td>  14</td>\n",
       "      <td> 105000</td>\n",
       "      <td> 142700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fire Command Staff III</th>\n",
       "      <td>  422655.0</td>\n",
       "      <td> 140885.000000</td>\n",
       "      <td>     0.000000</td>\n",
       "      <td>   3</td>\n",
       "      <td> 140885</td>\n",
       "      <td> 140885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public Health Physician II</th>\n",
       "      <td>  250600.0</td>\n",
       "      <td> 125300.000000</td>\n",
       "      <td> 10323.759005</td>\n",
       "      <td>   2</td>\n",
       "      <td> 118000</td>\n",
       "      <td> 132600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WWW Division Manager II</th>\n",
       "      <td>  441600.0</td>\n",
       "      <td> 110400.000000</td>\n",
       "      <td> 13499.629625</td>\n",
       "      <td>   4</td>\n",
       "      <td> 103000</td>\n",
       "      <td> 130600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIRE COMMAND STAFF II</th>\n",
       "      <td>  777522.0</td>\n",
       "      <td> 129587.000000</td>\n",
       "      <td>     0.000000</td>\n",
       "      <td>   6</td>\n",
       "      <td> 129587</td>\n",
       "      <td> 129587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WWW Chief of Engineering</th>\n",
       "      <td>  127296.0</td>\n",
       "      <td> 127296.000000</td>\n",
       "      <td>          NaN</td>\n",
       "      <td>   1</td>\n",
       "      <td> 127296</td>\n",
       "      <td> 127296</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  sum           mean           std  size    amin    amax\n",
       "JobTitle                                                                                \n",
       "STATE'S ATTORNEY             238772.0  238772.000000           NaN     1  238772  238772\n",
       "EXECUTIVE LEVEL III         1939968.0  161664.000000  23053.267708    12  132600  200000\n",
       "CONTRACT SERV SPEC II       6205482.0   55905.243243  28837.184910   111   15392  187200\n",
       "MAYOR                        163365.0  163365.000000           NaN     1  163365  163365\n",
       "CITY SOLICITOR               163200.0  163200.000000           NaN     1  163200  163200\n",
       "DIRECTOR PUBLIC WORKS        163200.0  163200.000000           NaN     1  163200  163200\n",
       "CONTRACT SERVICES SPEC. I   5366446.0   44350.793388  22709.853783   121   15392  156000\n",
       "CITY AUDITOR                 153600.0  153600.000000           NaN     1  153600  153600\n",
       "EXECUTIVE LEVEL II          9653928.4  116312.390361  16394.384734    83   80000  150756\n",
       "POLICE COMMAND STAFF II     1631204.0  116514.571429  12626.188424    14  105000  142700\n",
       "Fire Command Staff III       422655.0  140885.000000      0.000000     3  140885  140885\n",
       "Public Health Physician II   250600.0  125300.000000  10323.759005     2  118000  132600\n",
       "WWW Division Manager II      441600.0  110400.000000  13499.629625     4  103000  130600\n",
       "FIRE COMMAND STAFF II        777522.0  129587.000000      0.000000     6  129587  129587\n",
       "WWW Chief of Engineering     127296.0  127296.000000           NaN     1  127296  127296"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = dataframe.groupby(['JobTitle'])['AnnualSalary']\n",
    "aggregated = grouped.agg([np.sum, np.mean, np.std, np.size, np.min, np.max])\n",
    "\n",
    "# sort the data\n",
    "pd.set_option('display.max_rows', 10000000)\n",
    "output = aggregated.sort(['amax'],ascending=0)\n",
    "output.head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets take a look at the data when grouped by JobTitle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/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>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>size</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobTitle</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>POLICE OFFICER</th>\n",
       "      <td> 113057468.0</td>\n",
       "      <td>  60588.139335</td>\n",
       "      <td>  8284.120895</td>\n",
       "      <td> 1866</td>\n",
       "      <td> 43999</td>\n",
       "      <td>  71291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIDE BLUE CHIP</th>\n",
       "      <td>  54499380.0</td>\n",
       "      <td>  11313.967200</td>\n",
       "      <td>   117.949225</td>\n",
       "      <td> 4817</td>\n",
       "      <td> 11310</td>\n",
       "      <td>  15600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EMT Firefighter Suppression</th>\n",
       "      <td>  22000418.0</td>\n",
       "      <td>  61453.681564</td>\n",
       "      <td>  6562.939105</td>\n",
       "      <td>  358</td>\n",
       "      <td> 47475</td>\n",
       "      <td>  75197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LABORER (Hourly)</th>\n",
       "      <td>  17865623.0</td>\n",
       "      <td>  29925.666667</td>\n",
       "      <td>  1297.986721</td>\n",
       "      <td>  597</td>\n",
       "      <td> 28309</td>\n",
       "      <td>  33613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POLICE SERGEANT</th>\n",
       "      <td>  17320452.0</td>\n",
       "      <td>  78020.054054</td>\n",
       "      <td>  3299.578516</td>\n",
       "      <td>  222</td>\n",
       "      <td> 69528</td>\n",
       "      <td>  82704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POLICE OFFICER (EID)</th>\n",
       "      <td>  16235687.0</td>\n",
       "      <td>  64942.748000</td>\n",
       "      <td>  4487.637577</td>\n",
       "      <td>  250</td>\n",
       "      <td> 54463</td>\n",
       "      <td>  73012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fire Lieutenant Suppression</th>\n",
       "      <td>  10862692.0</td>\n",
       "      <td>  82293.121212</td>\n",
       "      <td>  3538.303326</td>\n",
       "      <td>  132</td>\n",
       "      <td> 73821</td>\n",
       "      <td>  86247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASSISTANT STATE'S ATTORNEY</th>\n",
       "      <td>  10462600.0</td>\n",
       "      <td>  69750.666667</td>\n",
       "      <td> 12861.042296</td>\n",
       "      <td>  150</td>\n",
       "      <td> 55000</td>\n",
       "      <td>  94900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Firefighter/Paramedic Suppress</th>\n",
       "      <td>  10096356.0</td>\n",
       "      <td>  67760.778523</td>\n",
       "      <td>  2859.659273</td>\n",
       "      <td>  149</td>\n",
       "      <td> 47476</td>\n",
       "      <td>  77305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXECUTIVE LEVEL II</th>\n",
       "      <td>   9653928.4</td>\n",
       "      <td> 116312.390361</td>\n",
       "      <td> 16394.384734</td>\n",
       "      <td>   83</td>\n",
       "      <td> 80000</td>\n",
       "      <td> 150756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Firefighter Suppression</th>\n",
       "      <td>   8465726.0</td>\n",
       "      <td>  72980.396552</td>\n",
       "      <td>  2251.335561</td>\n",
       "      <td>  116</td>\n",
       "      <td> 68825</td>\n",
       "      <td>  77305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXECUTIVE LEVEL I</th>\n",
       "      <td>   8134940.0</td>\n",
       "      <td>  87472.473118</td>\n",
       "      <td> 13204.216118</td>\n",
       "      <td>   93</td>\n",
       "      <td> 56300</td>\n",
       "      <td> 122400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fire Pump Operator Suppression</th>\n",
       "      <td>   7829100.0</td>\n",
       "      <td>  71826.605505</td>\n",
       "      <td>  4289.341133</td>\n",
       "      <td>  109</td>\n",
       "      <td> 63976</td>\n",
       "      <td>  77379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fire Emergency Veh Drvr Suppr</th>\n",
       "      <td>   7532487.0</td>\n",
       "      <td>  70397.074766</td>\n",
       "      <td>  4238.103761</td>\n",
       "      <td>  107</td>\n",
       "      <td> 63590</td>\n",
       "      <td>  76911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POLICE OFFICER TRAINEE</th>\n",
       "      <td>   7214048.0</td>\n",
       "      <td>  44531.160494</td>\n",
       "      <td>  2758.261395</td>\n",
       "      <td>  162</td>\n",
       "      <td> 43999</td>\n",
       "      <td>  62380</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        sum           mean           std  size   amin    amax\n",
       "JobTitle                                                                                     \n",
       "POLICE OFFICER                  113057468.0   60588.139335   8284.120895  1866  43999   71291\n",
       "AIDE BLUE CHIP                   54499380.0   11313.967200    117.949225  4817  11310   15600\n",
       "EMT Firefighter Suppression      22000418.0   61453.681564   6562.939105   358  47475   75197\n",
       "LABORER (Hourly)                 17865623.0   29925.666667   1297.986721   597  28309   33613\n",
       "POLICE SERGEANT                  17320452.0   78020.054054   3299.578516   222  69528   82704\n",
       "POLICE OFFICER (EID)             16235687.0   64942.748000   4487.637577   250  54463   73012\n",
       "Fire Lieutenant Suppression      10862692.0   82293.121212   3538.303326   132  73821   86247\n",
       "ASSISTANT STATE'S ATTORNEY       10462600.0   69750.666667  12861.042296   150  55000   94900\n",
       "Firefighter/Paramedic Suppress   10096356.0   67760.778523   2859.659273   149  47476   77305\n",
       "EXECUTIVE LEVEL II                9653928.4  116312.390361  16394.384734    83  80000  150756\n",
       "Firefighter Suppression           8465726.0   72980.396552   2251.335561   116  68825   77305\n",
       "EXECUTIVE LEVEL I                 8134940.0   87472.473118  13204.216118    93  56300  122400\n",
       "Fire Pump Operator Suppression    7829100.0   71826.605505   4289.341133   109  63976   77379\n",
       "Fire Emergency Veh Drvr Suppr     7532487.0   70397.074766   4238.103761   107  63590   76911\n",
       "POLICE OFFICER TRAINEE            7214048.0   44531.160494   2758.261395   162  43999   62380"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output = aggregated.sort(['sum','size'],ascending=[0,1])\n",
    "output.head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now lets graph it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "aggregated = grouped.agg([np.sum])\n",
    "output = aggregated.sort(['sum'],ascending=0)\n",
    "output = output.head(15)\n",
    "output.rename(columns={'sum': 'Salary'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1gXtRDwrgcyjg4aNIEb6ITHbTgA2IFdfp7vM24ER33WnAhm7/XsC2wMHuOyeh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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe1007bea50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.ticker import FormatStrFormatter\n",
    "\n",
    "myplot = output.plot(kind='bar',title='Baltimore Total Annual Salary by Job Title - 2014')\n",
    "myplot.set_ylabel('$')\n",
    "myplot.yaxis.set_major_formatter(FormatStrFormatter('%d'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}