{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyse the demographics of the workshop\n",
    "\n",
    "Who came, with what level, and how many stayed to the end. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set some default parameters for the matplotlib figures. I want to use the [seaborn](http://seaborn.pydata.org/) style sheet with larger text, all figures to have the same size, and have a white (instead of transparent) background. Also use a higher DPI when saving figures for better quality images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.style.use(['seaborn', 'seaborn-talk'])\n",
    "plt.rc('figure', facecolor='#ffffff')\n",
    "plt.rc('figure', figsize=(10, 5))\n",
    "plt.rc('figure', dpi=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the demographics data\n",
    "\n",
    "Data from the Google forms sign up. I exported the data (without names and emails) to the file `demographics.csv` in this repository. \n",
    "\n",
    "I'll use `pandas` library to load and manipulate the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('demographics.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>os</th>\n",
       "      <th>experience</th>\n",
       "      <th>languages</th>\n",
       "      <th>position</th>\n",
       "      <th>field</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Did a little bit of shell scripting</td>\n",
       "      <td>Python, Matlab/Octave</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Geophysics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course, Self-taught w...</td>\n",
       "      <td>C/C++, Fortran, Matlab/Octave</td>\n",
       "      <td>Faculty</td>\n",
       "      <td>Plate Tectonics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course, Took intermed...</td>\n",
       "      <td>C/C++, Matlab/Octave, JAVA, VRML, MEL, UnrealS...</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>GG (Hydrology)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>Matlab/Octave</td>\n",
       "      <td>Staff</td>\n",
       "      <td>Geology and Geophysics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>C/C++, Matlab/Octave</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Geochemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>Matlab/Octave, I use matlab from time to time ...</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Coastal Geology &amp; sea-level rise</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Self-taught with moderate/advanced experience</td>\n",
       "      <td>Fortran, Matlab/Octave, R</td>\n",
       "      <td>Postdoc</td>\n",
       "      <td>Watershed hydrology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Did a little bit of shell scripting</td>\n",
       "      <td>Matlab/Octave</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Mineral Physics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course, Took intermed...</td>\n",
       "      <td>Python, C/C++, Matlab/Octave</td>\n",
       "      <td>Faculty</td>\n",
       "      <td>Mineral Physics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took intermediate/advanced programming course</td>\n",
       "      <td>Matlab/Octave, R</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>geophysics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Self-taught with little experience</td>\n",
       "      <td>Python</td>\n",
       "      <td>Staff</td>\n",
       "      <td>Geomorphology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Never programmed before</td>\n",
       "      <td>None (I told I've never programmed before)</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Hydrology modeling</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took intermediate/advanced programming course,...</td>\n",
       "      <td>C/C++, Matlab/Octave, R, Java</td>\n",
       "      <td>Faculty</td>\n",
       "      <td>Coastal Geology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Never programmed before, Self-taught with litt...</td>\n",
       "      <td>Javascript</td>\n",
       "      <td>Undergraduate student</td>\n",
       "      <td>Geophysics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Took a basic programming course, Self-taught w...</td>\n",
       "      <td>Matlab/Octave, IDL, google engine</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>volcanology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Took a basic programming course, Self-taught w...</td>\n",
       "      <td>Matlab/Octave</td>\n",
       "      <td>Faculty</td>\n",
       "      <td>Volcanology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>Python, Matlab/Octave</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Coastal Hydrology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Never programmed before</td>\n",
       "      <td>None (I told I've never programmed before)</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Hydrology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course, Self-taught w...</td>\n",
       "      <td>Python</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Voclanology/Remote Sensing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>javascript, html</td>\n",
       "      <td>Undergraduate student</td>\n",
       "      <td>Geology and Geophysics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Self-taught with moderate/advanced experience</td>\n",
       "      <td>Matlab/Octave, R</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Planetary sciences</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Never programmed before, Did a little bit of s...</td>\n",
       "      <td>Python</td>\n",
       "      <td>Undergraduate student</td>\n",
       "      <td>Conservation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Took a basic programming course, Self-taught w...</td>\n",
       "      <td>C/C++, R</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Environmental science</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Self-taught with little experience</td>\n",
       "      <td>Python, Matlab/Octave</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Electrical Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>Fortran, Matlab/Octave, R</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>natural resources and environmental management</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>GNU/Linux</td>\n",
       "      <td>Self-taught with moderate/advanced experience</td>\n",
       "      <td>Python, Matlab/Octave, R, Bash Shell(?)</td>\n",
       "      <td>Marine Geophysical Data Tech</td>\n",
       "      <td>Marine Geophysics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Self-taught with moderate/advanced experience</td>\n",
       "      <td>Python, Matlab/Octave, R</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>ecohydrology (in the Geography Department)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Never programmed before</td>\n",
       "      <td>None (I told I've never programmed before)</td>\n",
       "      <td>Interested citizen</td>\n",
       "      <td>Film production and education</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Self-taught with little experience</td>\n",
       "      <td>Python</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Geography</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>GNU/Linux</td>\n",
       "      <td>Took intermediate/advanced programming course</td>\n",
       "      <td>Python, C/C++, Fortran</td>\n",
       "      <td>Na Kupuna student</td>\n",
       "      <td>civil engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Did a little bit of shell scripting, Took a ba...</td>\n",
       "      <td>Fortran, BASIC (yes, really)</td>\n",
       "      <td>Faculty</td>\n",
       "      <td>Geo Oceanography -- a lot of seafloor mapping</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Never programmed before</td>\n",
       "      <td>None (I told I've never programmed before)</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Geochemistry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Took a basic programming course</td>\n",
       "      <td>Matlab/Octave</td>\n",
       "      <td>Graduate student</td>\n",
       "      <td>Mineral physics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Windows</td>\n",
       "      <td>Did a little bit of shell scripting</td>\n",
       "      <td>R, bit of awk/sed for GMT tasks</td>\n",
       "      <td>gov't researcher</td>\n",
       "      <td>marine geology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Mac (OSX)</td>\n",
       "      <td>Never programmed before</td>\n",
       "      <td>None (I told I've never programmed before)</td>\n",
       "      <td>Undergraduate student</td>\n",
       "      <td>Geology</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           os                                         experience  \\\n",
       "0   Mac (OSX)                Did a little bit of shell scripting   \n",
       "1   Mac (OSX)  Took a basic programming course, Self-taught w...   \n",
       "2   Mac (OSX)  Took a basic programming course, Took intermed...   \n",
       "3     Windows                    Took a basic programming course   \n",
       "4   Mac (OSX)                    Took a basic programming course   \n",
       "5   Mac (OSX)                    Took a basic programming course   \n",
       "6     Windows      Self-taught with moderate/advanced experience   \n",
       "7     Windows                Did a little bit of shell scripting   \n",
       "8   Mac (OSX)  Took a basic programming course, Took intermed...   \n",
       "9   Mac (OSX)      Took intermediate/advanced programming course   \n",
       "10    Windows                 Self-taught with little experience   \n",
       "11  Mac (OSX)                            Never programmed before   \n",
       "12  Mac (OSX)  Took intermediate/advanced programming course,...   \n",
       "13  Mac (OSX)  Never programmed before, Self-taught with litt...   \n",
       "14    Windows  Took a basic programming course, Self-taught w...   \n",
       "15    Windows  Took a basic programming course, Self-taught w...   \n",
       "16  Mac (OSX)                    Took a basic programming course   \n",
       "17    Windows                            Never programmed before   \n",
       "18  Mac (OSX)  Took a basic programming course, Self-taught w...   \n",
       "19  Mac (OSX)                    Took a basic programming course   \n",
       "20  Mac (OSX)      Self-taught with moderate/advanced experience   \n",
       "21  Mac (OSX)  Never programmed before, Did a little bit of s...   \n",
       "22    Windows  Took a basic programming course, Self-taught w...   \n",
       "23    Windows                 Self-taught with little experience   \n",
       "24    Windows                    Took a basic programming course   \n",
       "25  GNU/Linux      Self-taught with moderate/advanced experience   \n",
       "26    Windows      Self-taught with moderate/advanced experience   \n",
       "27  Mac (OSX)                            Never programmed before   \n",
       "28  Mac (OSX)                 Self-taught with little experience   \n",
       "29  GNU/Linux      Took intermediate/advanced programming course   \n",
       "30  Mac (OSX)  Did a little bit of shell scripting, Took a ba...   \n",
       "31    Windows                            Never programmed before   \n",
       "32  Mac (OSX)                    Took a basic programming course   \n",
       "33    Windows                Did a little bit of shell scripting   \n",
       "34  Mac (OSX)                            Never programmed before   \n",
       "\n",
       "                                            languages  \\\n",
       "0                               Python, Matlab/Octave   \n",
       "1                       C/C++, Fortran, Matlab/Octave   \n",
       "2   C/C++, Matlab/Octave, JAVA, VRML, MEL, UnrealS...   \n",
       "3                                       Matlab/Octave   \n",
       "4                                C/C++, Matlab/Octave   \n",
       "5   Matlab/Octave, I use matlab from time to time ...   \n",
       "6                           Fortran, Matlab/Octave, R   \n",
       "7                                       Matlab/Octave   \n",
       "8                        Python, C/C++, Matlab/Octave   \n",
       "9                                    Matlab/Octave, R   \n",
       "10                                             Python   \n",
       "11         None (I told I've never programmed before)   \n",
       "12                      C/C++, Matlab/Octave, R, Java   \n",
       "13                                         Javascript   \n",
       "14                  Matlab/Octave, IDL, google engine   \n",
       "15                                      Matlab/Octave   \n",
       "16                              Python, Matlab/Octave   \n",
       "17         None (I told I've never programmed before)   \n",
       "18                                             Python   \n",
       "19                                   javascript, html   \n",
       "20                                   Matlab/Octave, R   \n",
       "21                                             Python   \n",
       "22                                           C/C++, R   \n",
       "23                              Python, Matlab/Octave   \n",
       "24                          Fortran, Matlab/Octave, R   \n",
       "25            Python, Matlab/Octave, R, Bash Shell(?)   \n",
       "26                           Python, Matlab/Octave, R   \n",
       "27         None (I told I've never programmed before)   \n",
       "28                                             Python   \n",
       "29                             Python, C/C++, Fortran   \n",
       "30                       Fortran, BASIC (yes, really)   \n",
       "31         None (I told I've never programmed before)   \n",
       "32                                      Matlab/Octave   \n",
       "33                    R, bit of awk/sed for GMT tasks   \n",
       "34         None (I told I've never programmed before)   \n",
       "\n",
       "                        position  \\\n",
       "0               Graduate student   \n",
       "1                        Faculty   \n",
       "2               Graduate student   \n",
       "3                          Staff   \n",
       "4               Graduate student   \n",
       "5               Graduate student   \n",
       "6                        Postdoc   \n",
       "7               Graduate student   \n",
       "8                        Faculty   \n",
       "9               Graduate student   \n",
       "10                         Staff   \n",
       "11              Graduate student   \n",
       "12                       Faculty   \n",
       "13         Undergraduate student   \n",
       "14              Graduate student   \n",
       "15                       Faculty   \n",
       "16              Graduate student   \n",
       "17              Graduate student   \n",
       "18              Graduate student   \n",
       "19         Undergraduate student   \n",
       "20              Graduate student   \n",
       "21         Undergraduate student   \n",
       "22              Graduate student   \n",
       "23              Graduate student   \n",
       "24              Graduate student   \n",
       "25  Marine Geophysical Data Tech   \n",
       "26              Graduate student   \n",
       "27            Interested citizen   \n",
       "28              Graduate student   \n",
       "29             Na Kupuna student   \n",
       "30                       Faculty   \n",
       "31              Graduate student   \n",
       "32              Graduate student   \n",
       "33              gov't researcher   \n",
       "34         Undergraduate student   \n",
       "\n",
       "                                             field  \n",
       "0                                       Geophysics  \n",
       "1                                  Plate Tectonics  \n",
       "2                                   GG (Hydrology)  \n",
       "3                           Geology and Geophysics  \n",
       "4                                     Geochemistry  \n",
       "5                 Coastal Geology & sea-level rise  \n",
       "6                              Watershed hydrology  \n",
       "7                                  Mineral Physics  \n",
       "8                                  Mineral Physics  \n",
       "9                                       geophysics  \n",
       "10                                   Geomorphology  \n",
       "11                              Hydrology modeling  \n",
       "12                                 Coastal Geology  \n",
       "13                                      Geophysics  \n",
       "14                                     volcanology  \n",
       "15                                     Volcanology  \n",
       "16                               Coastal Hydrology  \n",
       "17                                       Hydrology  \n",
       "18                      Voclanology/Remote Sensing  \n",
       "19                          Geology and Geophysics  \n",
       "20                              Planetary sciences  \n",
       "21                                    Conservation  \n",
       "22                           Environmental science  \n",
       "23                          Electrical Engineering  \n",
       "24  natural resources and environmental management  \n",
       "25                               Marine Geophysics  \n",
       "26      ecohydrology (in the Geography Department)  \n",
       "27                   Film production and education  \n",
       "28                                       Geography  \n",
       "29                               civil engineering  \n",
       "30   Geo Oceanography -- a lot of seafloor mapping  \n",
       "31                                    Geochemistry  \n",
       "32                                 Mineral physics  \n",
       "33                                  marine geology  \n",
       "34                                         Geology  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Attendance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First lets see the number of people who signed up:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the shared notes, I also know how many people showed up after each day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "attendance = pd.Series([len(data), 31, 21, 21], index=['Signed up', 'Day 1', 'Day 2', 'Day 3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcb4502dac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "ax = plt.subplot(111)\n",
    "attendance.plot.barh(ax=ax)\n",
    "ax.invert_yaxis()\n",
    "ax.set_title('Attendance for the workshop')\n",
    "ax.set_xlabel('Participants')\n",
    "plt.tight_layout()\n",
    "plt.savefig('figures/attendance.jpg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " We had a bit of a drop off after the first day. The people who came the seconda day also came on the third. Not too bad."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Programming experience\n",
    "\n",
    "Let's first look at the programming experience declared by the participants. I'll keep only the highest level declared and count how many people declared that level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Keep only the last (highest) element in the declared experience\n",
    "data['highest_experience'] = pd.Series([e.split(', ')[-1] for e in data['experience']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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XrwYA5ObmYu/evRrbM3v2bFSoUPwX1ktrzBRkY2OD4cOHK203NDQU30AA8vKAyxMEQewz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\nA1CWihqPkvD09DRmlX/00UfKyspSgwYNCixS2bp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bKyslClShVYW1ujf//+GDBgALZt24bo6Ghc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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcb41c6de80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "ax = plt.subplot(111)\n",
    "data.highest_experience.value_counts().plot.barh(ax=ax)\n",
    "ax.invert_yaxis()\n",
    "ax.set_title('Highest experience declared')\n",
    "ax.set_xlabel('Participants')\n",
    "plt.tight_layout()\n",
    "plt.savefig('figures/education.jpg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The workshop participants have very mixed experience levels, from people who have never programmed before to self-taught programmers. That was expected and it's also not surprising that very few people indicated that they reached their level by taking an advanced course."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Programming languages\n",
    "\n",
    "Let's look at the programming language experience. I'll focus on a few main languages and group the others into \"Others\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "main_languages = ['Python', 'Matlab/Octave', 'C/C++', 'Fortran', 'R', \"None (I told I've never programmed before)\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a function to mark any other language as \"Other\" and simplify the \"None\" entry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def only_main(lang):\n",
    "    if lang not in main_languages:\n",
    "        lang = 'Other'\n",
    "    if lang == \"None (I told I've never programmed before)\":\n",
    "        lang = 'None'\n",
    "    return lang"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "languages = pd.Series([only_main(lang) \n",
    "                       for entry in data['languages'] \n",
    "                       for lang in entry.split(', ')]).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Matlab/Octave    20\n",
       "Other            15\n",
       "Python           11\n",
       "R                 9\n",
       "C/C++             7\n",
       "Fortran           5\n",
       "None              5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ksN+aNWuktgcGBgrbTExMRAsXLlRYV3h4uMjU1FRkYmIiMjMzE7m6usot5+XlJWrTpo1Q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\n2bPh8TPPPJNvfvObGTNmTPbaa68kyaGHHpoxY8Z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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcb40e81160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "ax = plt.subplot(111)\n",
    "languages.plot.barh(ax=ax)\n",
    "ax.invert_yaxis()\n",
    "ax.set_title('Programming language experience')\n",
    "ax.set_xlabel('Participants')\n",
    "ax.set_xticks(range(0, 22, 3))\n",
    "plt.tight_layout()\n",
    "plt.savefig('figures/programming-languages.jpg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dominant language in the department is clearly Matlab, though a few people also know R. Fortran is very low here apparently."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Position at the University\n",
    "\n",
    "Finally, we can look at what the participants do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcb41aed5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "ax = plt.subplot(111)\n",
    "data['position'].value_counts().plot.barh(ax=ax)\n",
    "ax.invert_yaxis()\n",
    "ax.set_title('Position')\n",
    "ax.set_xlabel('Participants')\n",
    "ax.set_xticks(range(0, 22, 3))\n",
    "plt.tight_layout()\n",
    "plt.savefig('figures/position.jpg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not surprisingly, a majority are grad students. I was very pleased to have someone from the [Na Kupuna program](https://www.hawaii.edu/diversity/seed-programs/na-kupuna-senior-citizen-visitor-program/) and a not insignificant number of faculty."
   ]
  }
 ],
 "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": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}