{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MIT Astrophysics Alumni: Where are they now?\n",
    "In this project, we gathered the data for all MIT astrophysics alumni who finished their PhD since 2002 (data from <a href=\"http://space.mit.edu/people/mki-alumni \">MIT Astro Website</a>) and created a quick data visualization to see the data in a quick glance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import subprocess\n",
    "import pickle\n",
    "import matplotlib.pyplot as plt\n",
    "import mpld3\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from astropy.io import fits\n",
    "from statsmodels.graphics.mosaicplot import mosaic\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df=pd.read_csv('mki_data.csv')\n",
    "df=df.replace('n/a', np.nan)\n",
    "df=df.replace('Reppaport','Rappaport')\n",
    "df=df.replace('Burles','Burke')\n",
    "df2=df.groupby(['Career Type'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Career Type of MIT Astrophysics Alumni after graduating from MIT\n",
    "- There is also a detail for each individual with their company name, title and year they graduated. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x135650f10>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA20AAAHLCAYAAABbKHAQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1348c3510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_COLORS=7\n",
    "cm = plt.get_cmap('Set2')\n",
    "df2=df.groupby(['Career Type'])\n",
    "bins=np.arange(13)+2002.-0.5\n",
    "y=[group['Year'] for name, group in df2]\n",
    "names=[str(name) for name, group in df2]\n",
    "\n",
    "fig,ax=plt.subplots(figsize=(15,7))\n",
    "ax.set_color_cycle([cm(1.*i/NUM_COLORS) for i in range(NUM_COLORS)])\n",
    "plot=ax.hist(y, bins=bins, stacked=True, normed = True, label=names)\n",
    "box=ax.get_position()\n",
    "ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])\n",
    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "plt.suptitle(\"Career Type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--Academic--\n",
      "('University of Michigan', 'Associate Professor')\n",
      "('Arizona State University', 'Assistant Professor')\n",
      "('University of Michigan', 'Associate Professor(also CFA affiliate)')\n",
      "('Sam Houston State University', 'Assistant Professor')\n",
      "('Mount Holyoke College', 'Assistant Professor')\n",
      "('Caltech', 'Professor')\n",
      "('University of California, Santa Cruz', 'Assistant Professor')\n",
      "('Shanghai Astronomical Observatory', 'Professor')\n",
      "('University of Utah', 'Assistant Professor')\n",
      "('Tennessee State University', 'Assistant Professor')\n",
      "('Syracuse Univesity', 'Professor')\n",
      "('Arizona State University', 'Assistant Professor')\n",
      "('University of Tokyo', 'Professor')\n",
      "('Louisiana State University', 'Assistant Professor')\n",
      "('UC Davis', 'Lecturer')\n",
      "('Georgia Tech', 'Assistant Professor')\n",
      "('NC State University', 'Assistant Professor')\n",
      "\n",
      "--K-12--\n",
      "('Westport Board of Education, CT', 'Physics & Science Research Teacher')\n",
      "('Acera School', 'Specialist')\n",
      "\n",
      "--Medical Industry--\n",
      "('MGH/Harvard Medical School', 'Instructor in Radiology')\n",
      "('San Fransicso Paramedic Association', 'EMT Program Director')\n",
      "('Harvard Medical School', 'Medical Physics Resident')\n",
      "\n",
      "--Nonprofit--\n",
      "('Institute for Defense Analyses', 'Research Staff')\n",
      "('Institute for Defense Analyses', 'Research Staff')\n",
      "\n",
      "--Outside Industry--\n",
      "('Danske Bank', 'Senior Portfolio Manager')\n",
      "('IBM Canada', 'Principal Engineer')\n",
      "('The Moving Picture Company', 'R&D Software Engineer')\n",
      "('Metron, Inc.', 'Analyst')\n",
      "('Canadian Imperial Bank of Commerce', 'Senior Analyst')\n",
      "('Origin Energy', 'Senior Analyst')\n",
      "('HP Autonomy', 'Systems Performance Engineer')\n",
      "('Rbs Securities', 'Advisor')\n",
      "('Arete Associates', 'Staff Scientist')\n",
      "('Microsoft Bing Search', 'Program Manager')\n",
      "('Morgan Stanley', 'Desk Strategist, Vice President')\n",
      "('J.P. Morgan', 'Associate')\n",
      "('Goldman Sachs', 'Broker')\n",
      "('HP Autonomy', 'Technology Consultant')\n",
      "('WegoWise', 'Data Scientist')\n",
      "('Waters Pacific Pte Ltd', 'Senior Engineering Manager(R&D)')\n",
      "('Eyekon Systems LLC', 'Founder')\n",
      "('Smith&Nephew, Endoscopy', 'Development Engineer')\n",
      "('GE Global Research', 'Optical Scientist')\n",
      "('UBS London', 'Associate Director')\n",
      "('Intel', 'Senior Process Engineer')\n",
      "('Intellectual Ventures', 'Research Analyst')\n",
      "('Izentis LLC', 'CEO')\n",
      "('Lam Research', 'Mechanical Engineer')\n",
      "\n",
      "--Postdoc--\n",
      "('Jet Propulsion Laboratory', 'Postdoctoral Associate')\n",
      "('NRAO', 'Postdoctoral Fellow')\n",
      "('Harvard- CfA', 'Hubble Fellow')\n",
      "('Northwestern University', 'Postdoctoral Fellow')\n",
      "('University of Florida', 'Postdoctoral Associate')\n",
      "('University of Alabama', 'Postdoctoral Associate')\n",
      "('Yale University', 'Postdoctoral Fellow')\n",
      "('NASA', 'Postdoctoral Fellow')\n",
      "('Astronomical Institute Anton Pannekoek', 'Postdoc')\n",
      "('Purdue University', 'Postdoctoral Researcher')\n",
      "('Kapteyn Astronomical Institute', 'Postdoctoral Researcher')\n",
      "('UC Berkeley', 'Postdoctoral Fellow')\n",
      "('Caltech', 'Hubble Fellow')\n",
      "('Caltech-LIGO', 'Postdoctoral Fellow')\n",
      "('Cornell University', 'Einstein Fellow')\n",
      "('Jet Propulsion Laboratory', 'NASA Postdoctoral Fellow')\n",
      "('UC Berkeley', 'Postdoctoral Fellow')\n",
      "('LIGO Hanford Observatory', 'Postdoc')\n",
      "('MIT-LIGO', 'Postdoctoral Associate')\n",
      "(\"Institut d'Astrophysique de Paris\", 'Postdoctoral Fellow')\n",
      "('MIT', 'Postdoctoral Fellow')\n",
      "('Stanford University', 'Postdoctoral Scholar')\n",
      "('Yale University', 'Postdoctoral Associate')\n",
      "\n",
      "--Scientific Research --\n",
      "('MIT Lincoln Laboratory', 'Technical Staff')\n",
      "('MIT-Lincoln Lab', 'Technical Staff')\n",
      "('MIT Lincoln Laboratory', 'Technical Staff')\n",
      "('NASA - Goddard', 'Astrophysicist')\n",
      "('UC Berkeley', 'Research Physicist')\n",
      "('Caltech', 'Research Physicist')\n",
      "('Boston University', 'Research Associate')\n",
      "('MIT Lincoln Laboratory', 'Technical Staff')\n",
      "('NASA, Ames for 3 yrs; currently, MIT', 'MechE PhD program')\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for name, group in df2:\n",
    "    print \"--\"+name+\"--\"\n",
    "    for i in zip(group['Company Name'].values,group['Title'].values):\n",
    "        print i\n",
    "    print \"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Area Study for MIT Alumni\n",
    "- ASTRT: Astrophysics Theory\n",
    "- ASTRX: Astrophysics Experiment\n",
    "- AeroAstro: Aeronautics and Astronautics\n",
    "- CTP: Center of Theoritical Physics\n",
    "- EECS: Electrical Engineering and Computer Science\n",
    "- MechE: Mechanical Engineering\n",
    "- NUPAX: Experimental High Energy and Nuclear Physics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x135b5ee90>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzMAAAHLCAYAAAD89cbrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x133583ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_COLORS = 7\n",
    "\n",
    "cm = plt.get_cmap('Paired')\n",
    "df2=df.groupby(['Area'])\n",
    "bins=np.arange(13)+2002.-0.5\n",
    "#n=np.arange(13)+2002.\n",
    "#x_label=['%i' % i for i in n]\n",
    "y=[group['Year'] for name, group in df2]\n",
    "names=[str(name) for name, group in df2]\n",
    "\n",
    "fig,ax=plt.subplots(figsize=(15,7))\n",
    "ax.set_color_cycle([cm(1.*i/NUM_COLORS) for i in range(NUM_COLORS)])\n",
    "ax.hist(y, bins=bins, alpha=1.0, stacked=True, normed = True, label=names)\n",
    "box=ax.get_position()\n",
    "ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])\n",
    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "plt.suptitle(\"Area Study\")\n",
    "#ax.set_xticklabels(x_label)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thesis Supervisor of MIT Alumni"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x133ea0a50>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2UAAAIACAYAAAACOMQOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIiIOUlEmIiIiIiLioP8HioQcdaiHDzUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1348d7950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_COLORS = 28\n",
    "\n",
    "cm = plt.get_cmap('Paired')\n",
    "df2=df.groupby(['Supervisor1'])\n",
    "bins=np.arange(13)+2002.-0.5\n",
    "y=[group['Year'] for name, group in df2]\n",
    "names=[str(name) for name, group in df2]\n",
    "\n",
    "fig,ax=plt.subplots(figsize=(15,7))\n",
    "ax.set_color_cycle([cm(1.*i/NUM_COLORS) for i in range(NUM_COLORS)])\n",
    "ax.hist(y, bins=bins, alpha=1.0, stacked=True, normed = True, label=names)\n",
    "box=ax.get_position()\n",
    "ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])\n",
    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "plt.suptitle(\"Supervisor\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "df3=df2=df.groupby(['Career Type','Year'])\n",
    "x=[group['Title'] for name, group in df3]\n",
    "\n",
    "[', '.join(group['Title'].values) for name, group in df3 if name[0]=='Academic']"
   ]
  }
 ],
 "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": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}