faq/median-vs-mean/mean-vs-median.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "data source: https://opendata.socrata.com/dataset/FGCU-salary-dataset/fjqw-ymup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Last Name</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Annual Salary</th>\n",
       "      <th>FGCU Hire Date</th>\n",
       "      <th>College/Dept</th>\n",
       "      <th>Class Title</th>\n",
       "      <th>Working Title</th>\n",
       "      <th>Employee Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gray-Vickrey</td>\n",
       "      <td>Margaret</td>\n",
       "      <td>$127972.27</td>\n",
       "      <td>07/01/1996</td>\n",
       "      <td>Academic Affairs Administration</td>\n",
       "      <td>Assoc. Vice President/Prof.</td>\n",
       "      <td>Assc. Provost/Assoc. VP C&amp;I</td>\n",
       "      <td>Faculty Admin 10, 11, 12 mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rogers</td>\n",
       "      <td>Hudson</td>\n",
       "      <td>$134316.57</td>\n",
       "      <td>08/07/1997</td>\n",
       "      <td>Academic Affairs Administration</td>\n",
       "      <td>Assoc. Vice President/Prof.</td>\n",
       "      <td>Associate VP &amp; Professor</td>\n",
       "      <td>Faculty Admin 10, 11, 12 mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hart</td>\n",
       "      <td>Erika</td>\n",
       "      <td>$26650.11</td>\n",
       "      <td>08/03/2001</td>\n",
       "      <td>Academic Affairs Administration</td>\n",
       "      <td>Program Asst</td>\n",
       "      <td>Program Assistant</td>\n",
       "      <td>Support Personnel NonExempt PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deschene</td>\n",
       "      <td>Catherine</td>\n",
       "      <td>$63960.27</td>\n",
       "      <td>01/05/2004</td>\n",
       "      <td>Academic Affairs Administration</td>\n",
       "      <td>Executive Asst</td>\n",
       "      <td>Exec Asst to Provost &amp; VPAA</td>\n",
       "      <td>Administrative/Professional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Baker</td>\n",
       "      <td>Jennifer</td>\n",
       "      <td>$90000.00</td>\n",
       "      <td>05/26/2009</td>\n",
       "      <td>Academic Affairs Administration</td>\n",
       "      <td>Dir, Academic Support Services</td>\n",
       "      <td>Dir., Budgets &amp; Management Svs</td>\n",
       "      <td>Administrative/Professional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Last Name First Name Annual Salary FGCU Hire Date  \\\n",
       "0  Gray-Vickrey   Margaret    $127972.27     07/01/1996   \n",
       "1        Rogers     Hudson    $134316.57     08/07/1997   \n",
       "2          Hart      Erika     $26650.11     08/03/2001   \n",
       "3      Deschene  Catherine     $63960.27     01/05/2004   \n",
       "4         Baker   Jennifer     $90000.00     05/26/2009   \n",
       "\n",
       "                      College/Dept                     Class Title  \\\n",
       "0  Academic Affairs Administration     Assoc. Vice President/Prof.   \n",
       "1  Academic Affairs Administration     Assoc. Vice President/Prof.   \n",
       "2  Academic Affairs Administration                    Program Asst   \n",
       "3  Academic Affairs Administration                  Executive Asst   \n",
       "4  Academic Affairs Administration  Dir, Academic Support Services   \n",
       "\n",
       "                    Working Title                  Employee Class  \n",
       "0     Assc. Provost/Assoc. VP C&I     Faculty Admin 10, 11, 12 mo  \n",
       "1        Associate VP & Professor     Faculty Admin 10, 11, 12 mo  \n",
       "2               Program Assistant  Support Personnel NonExempt PT  \n",
       "3     Exec Asst to Provost & VPAA     Administrative/Professional  \n",
       "4  Dir., Budgets & Management Svs     Administrative/Professional  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('./FGCU_salary_dataset.csv')\n",
    "df_m = df\n",
    "d = df_m['Annual Salary'].apply(lambda x: x.lstrip('$'))\n",
    "d = d.astype('float64')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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CLpdr7Mv169cRHh6O5s2bw9nZGRMmTKhRk191XnnpwYMH+PXXXyGTydCjRw9IJJLKiIu0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\niGAFAMAgghUAAIPeASF6+FkA2AEhAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106d8f5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "with plt.style.context('fivethirtyeight'):\n",
    "    plt.hist(d.values, bins=50, alpha=0.4)\n",
    "    plt.axvline(np.mean(d.values), ymin=0.0, ymax=600, linewidth=2, color='k', label='mean')\n",
    "    plt.axvline(x=np.median(d.values), ymin=0.0, ymax=600, linewidth=2, color='b', linestyle='--', label='median')\n",
    "    plt.legend(loc='upper right')\n",
    "    plt.ylabel('Number of Employees')\n",
    "    plt.xlabel('Annual Salary')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = np.random.normal(loc=0.0, scale=1.0, size=10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SZrMZS5YssbSPGzcOGo0G33//PYDLZ1wajQahoaFobGy0fPUG3yeffAIAOHr0KGQyGZYt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\nEZHkMeyIiEjyGHZERCR5DDsiIpK8/wf9gf6FpJtA2wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105f8df98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with plt.style.context('fivethirtyeight'):\n",
    "    plt.hist(data, bins=50, alpha=0.4)\n",
    "    plt.axvline(np.mean(data), ymin=0.0, ymax=600, linewidth=2, color='k', label='mean')\n",
    "    plt.axvline(x=np.median(data), ymin=0.0, ymax=600, linewidth=2, color='b', linestyle='--', label='median')\n",
    "    plt.legend(loc='upper right')\n",
    "    plt.ylabel('Count')\n",
    "    plt.xlabel('x')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0033737113299363549"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.016896725981360865"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.median(data)"
   ]
  },
  {
   "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
}