Participant_demographics_ghw2019.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2019 GHW participant demographics\n",
    "### A. Arendt\n",
    "\n",
    "Need this for the TRIPODS-X final report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function\n",
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import gspread\n",
    "from gspread_pandas import Spread, Client\n",
    "\n",
    "import entrofy\n",
    "import entrofy.mappers\n",
    "import entrofy.core\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "seed = 20220321"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read in the raw data collected from the Google Form and saved as a csv\n",
    "\n",
    "Must share editor access of your spreadsheet to:\n",
    "\n",
    "`hackweek-access@quickstart-1612812313306.iam.gserviceaccount.com`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gc = gspread.service_account()\n",
    "sh = gc.open('GHW 2019 applicants').sheet1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(sh.get_all_records())\n",
    "df.reset_index(inplace=True)\n",
    "df.reset_index(inplace=True)\n",
    "df.Timestamp = pd.to_datetime(df.Timestamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Last Name'] = df['Last Name'].str.capitalize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Identify duplicate entries for removal later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([43], dtype='int64')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s= df.duplicated(subset=['First Name','Last Name'])\n",
    "duplicates_idx = s[s].index\n",
    "duplicates_idx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Find those that we selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "sh = gc.open('Geohackweek 2019 Participants').worksheet('All Candidates & Instructors')\n",
    "selectedParticipants = pd.DataFrame(sh.get_all_records())\n",
    "selectedParticipants = selectedParticipants[selectedParticipants['accepted']=='YES']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "selectedParticipants = selectedParticipants.merge(df, on=['Last Name','First Name']) #['index'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We selected 55 participants total.\n"
     ]
    }
   ],
   "source": [
    "print('We selected ' + str(len(selectedParticipants)) + ' participants total.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### some functions to generate plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_plot_categorical(df, column_str):\n",
    "    ax = entrofy.plotting.plot_distribution(df, column_str,\n",
    "                                        xtype=\"categorical\",\n",
    "                                        cmap=\"YlGnBu\", ax=None)\n",
    "    ax.set_xticklabels(ax.xaxis.get_majorticklabels(), rotation='vertical')\n",
    "\n",
    "def make_plot_continuous(df, column_str):\n",
    "    ax = entrofy.plotting.plot_distribution(df, column_str,\n",
    "                                        xtype=\"continuous\",\n",
    "                                        cmap=\"YlGnBu\", ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Are you currently affiliated with the University of Washington?\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Are you currently affiliated with the University of Washington?\")\n",
    "make_plot_categorical(selectedParticipants, 'Are you currently affiliated with the University of Washington?')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What is your current position?\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"What is your current position?\")\n",
    "make_plot_categorical(selectedParticipants, 'Current Position')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Where are you geographically located?\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfEAAAG4CAYAAABVZd7ZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAeRUlEQVR4nO3debSddX3v8feHIKDIIJK2CmKwRVqqohgckNapttJLZSgVsFobB0pbhbartbrurV5vb9dttXWhrS3FymAnhDIYvSmKqyp1JgyCqHhTUEgRAScgipjwvX/s59STwxl2TvKcJ7+d92utvbKf336y81GP+eT3DL8nVYUkSWrPTkMHkCRJi2OJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjdp56ABbat99960VK1YMHUOSpCVz1VVX3VVVy2eON1fiK1asYO3atUPHkCRpyST56mzjHk6XJKlRlrgkSY2yxCVJapQlLklSoyxxSZIaZYlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGtXcU8yk7cnxF3xg6AjqycUvPnroCNKCnIlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJalSvJZ7khUluTLIuyetn+XyvJO9P8rkkNyRZ1WceSZImSW8lnmQZ8E7gKOAQ4OQkh8zY7beBL1TVocBzgL9IsktfmSRJmiR9zsSfBqyrqpuq6n7gfOCYGfsUsEeSAA8Hvgls7DGTJEkTo88S3w+4ddr2+m5sur8Cfgq4DbgeOL2qHpj5RUlOSbI2ydo777yzr7ySJDWlzxLPLGM1Y/sXgGuBRwNPBv4qyZ4P+k1VZ1XVyqpauXz58m2dU5KkJvVZ4uuBx0zb3p/RjHu6VcDFNbIOuBn4yR4zSZI0Mfos8SuBg5Ic2F2sdhKwesY+twDPB0jyo8DBwE09ZpIkaWLs3NcXV9XGJK8BPggsA86uqhuSnNp9fibwx8C5Sa5ndPj9D6vqrr4ySZI0SXorcYCqWgOsmTF25rT3twE/32cGSZImlSu2SZLUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJapQlLklSoyxxSZIaZYlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJapQlLklSoyxxSZIaZYlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJalSvJZ7khUluTLIuyevn2Oc5Sa5NckOSj/WZR5KkSbJzX1+cZBnwTuAFwHrgyiSrq+oL0/bZG/hr4IVVdUuSH+krjyRJk6bPmfjTgHVVdVNV3Q+cDxwzY5+XABdX1S0AVXVHj3kkSZoofZb4fsCt07bXd2PTPR54RJKPJrkqya/N9kVJTkmyNsnaO++8s6e4kiS1pc8SzyxjNWN7Z+CpwH8DfgH4oySPf9BvqjqrqlZW1crly5dv+6SSJDWot3PijGbej5m2vT9w2yz73FVVG4ANSa4ADgW+3GMuSZImQp8z8SuBg5IcmGQX4CRg9Yx93gf8TJKdkzwMeDrwxR4zSZI0MXqbiVfVxiSvAT4ILAPOrqobkpzafX5mVX0xyWXAdcADwN9V1ef7yiRJ0iTp83A6VbUGWDNj7MwZ228F3tpnDkmSJtFYh9OTHJlkVfd+eZID+40lSZIWsmCJJ3kT8IfAG7qhhwD/0GcoSZK0sHFm4scBLwI2AFTVbcAefYaSJEkLG6fE76+qorvHO8nu/UaSJEnjGKfEL0jyt8DeSV4NfBh4V7+xJEnSQha8Or2q/jzJC4C7gYOBN1bV5b0nkyRJ8xrrFrOutC1uSZK2I3OWeJJ7ePBa5zBaE72qas/eUkmSpAXNWeJV5RXokiRtx8Y6nJ7kMOBIRjPzj1fVNb2mkiRJCxpnsZc3AucBjwT2Bc5N8j/6DiZJkuY3zkz8ZOApVXUfQJI/Ba4G/nefwSRJ0vzGuU/8K8Bu07Z3Bf6jlzSSJGls48zEvw/ckORyRufEXwB8PMk7AKrqtB7zSZKkOYxT4pd0rykf7SeKJEnaEuOs2HbeUgSRJElbZpyr049Ock2Sbya5O8k9Se5einCSJGlu4xxOPwM4Hri+e5qZJEnaDoxzdfqtwOctcEmSti/jzMRfB6xJ8jFGV6oDUFVv6y2VJEla0Dgl/ifAvYzuFd+l3ziSJGlc45T4PlX1870nkSRJW2Scc+IfTmKJS5K0nRmnxH8buCzJ97zFTJKk7cc4i734XHFJkrZD4z5P/BHAQUx7EEpVXdFXKEmStLAFSzzJq4DTgf2Ba4FnAJ8CntdrMkmSNK9xzomfDhwOfLWqngs8Bbiz11SSJGlB45T4fVV1H0CSXavqS8DB/caSJEkLGeec+PokewOXApcn+RZwW5+hJEnSwsa5Ov247u3/TPIRYC/gsl5TSZKkBY3zKNIfT7Lr1CawAnhYn6EkSdLCxjknfhGwKclPAO8GDgT+qddUkiRpQeOU+ANVtRE4Djijqn4XeFS/sSRJ0kLGKfEfJDkZeDnwgW7sIf1FkiRJ4xinxFcBzwT+pKpuTnIg8A/9xpIkSQsZ5+r0LwCnTdu+GfjTPkNJkqSFjTMTlyRJ2yFLXJKkRs1Z4kn+vvv19KWLI0mSxjXfTPypSR4LvCLJI5LsM/21VAElSdLs5ruw7UxGy6s+DriK0WptU6oblyRJA5lzJl5V76iqnwLOrqrHVdWB014WuCRJAxvnFrPfTHIo8DPd0BVVdV2/sSRJ0kLGeQDKacA/Aj/Svf4xyWv7DiZJkuY3zvPEXwU8vao2ACT5M+BTwF/2GUySJM1vnPvEA2yatr2JzS9ykyRJAxhnJn4O8Jkkl3TbxzJ6JKkkSRrQOBe2vS3JR4EjGc3AV1XVNX0HkyRJ8xtnJk5VXQ1c3XMWSZK0BVw7XZKkRlnikiQ1yhKXJKlR4yz2cnyS/5fkO0nuTnJPkruXIpwkSZrbOBe2vQX4par6Yt9hJEnS+MY5nP51C1ySpO3PODPxtUneC1wKfH9qsKou7iuUJEla2DglvifwXeDnp40VYIlLkjSgcVZsW7UUQSRJ0pYZ5+r0/ZNckuSOJF9PclGS/ZcinCRJmts4F7adA6wGHg3sB7y/G5MkSQMap8SXV9U5VbWxe50LLO85lyRJWsA4JX5XkpcmWda9Xgp8Y5wvT/LCJDcmWZfk9fPsd3iSTUlOGDe4JEk7unFK/BXAi4Hbga8BJ3Rj80qyDHgncBRwCHBykkPm2O/PgA+OH1uSJI1zdfotwIsW8d1PA9ZV1U0ASc4HjgG+MGO/1wIXAYcv4s+QJGmHNWeJJ3ldVb0lyV8yui98M1V12gLfvR9w67Tt9cDTZ/wZ+wHHAc9jnhJPcgpwCsABBxywwB8rSdKOYb6Z+NRSq2sX+d2ZZWzmPwbOAP6wqjYls+3e/aaqs4CzAFauXPmgf1BIkrQjmrPEq+r93dvvVtWF0z9L8itjfPd64DHTtvcHbpuxz0rg/K7A9wV+McnGqrp0jO+XJGmHNs6FbW8Yc2ymK4GDkhyYZBfgJEb3m/+XqjqwqlZU1QrgX4DfssAlSRrPfOfEjwJ+EdgvyTumfbQnsHGhL66qjUlew+iq82XA2VV1Q5JTu8/P3KrkkiTt4OY7J34bo/PhLwKumjZ+D/C743x5Va0B1swYm7W8q+rXx/lOSZI0Mt858c8Bn0tyCbChqjbBf93XvesS5ZMkSXMY55z4h4CHTtt+KPDhfuJIkqRxjVPiu1XVvVMb3fuH9RdJkiSNY5wS35DksKmNJE8FvtdfJEmSNI4Fl10Ffge4MMnUPd6PAk7sLZEkSRrLOGunX5nkJ4GDGa3C9qWq+kHvySRJ0rzGmYnDqMAPAXYDnpKEqnpPf7EkSdJCFizxJG8CnsOoxNcwerToxwFLXJKkAY1zYdsJwPOB26tqFXAo3icuSdLgxinx71XVA8DGJHsCdwCP6zeWJElayDjnxNcm2Rt4F6PlV+8FPttnKEmStLB5SzyjZ4T+n6r6NnBmksuAPavquqUIJ0mS5jbv4fSqKuDSadtfscAlSdo+jHNO/NNJDu89iSRJ2iLjnBN/LnBqkq8AGxgt+FJV9aQ+g0mSpPnNWeJJDqiqWxjdFy5JkrYz883ELwUOq6qvJrmoqn55iTJJkqQxzHdOPNPee1+4JEnbmflKvOZ4L0mStgPzHU4/NMndjGbkD+3eww8vbNuz93SSJGlOc5Z4VS1byiCSJGnLjHOfuCRJ2g5Z4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJapQlLklSoyxxSZIaZYlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRvVa4klemOTGJOuSvH6Wz381yXXd65NJDu0zjyRJk6S3Ek+yDHgncBRwCHBykkNm7HYz8OyqehLwx8BZfeWRJGnS9DkTfxqwrqpuqqr7gfOBY6bvUFWfrKpvdZufBvbvMY8kSROlzxLfD7h12vb6bmwurwT+tcc8kiRNlJ17/O7MMlaz7pg8l1GJHznH56cApwAccMAB2yqfJElN63Mmvh54zLTt/YHbZu6U5EnA3wHHVNU3ZvuiqjqrqlZW1crly5f3ElaSpNb0WeJXAgclOTDJLsBJwOrpOyQ5ALgYeFlVfbnHLJIkTZzeDqdX1cYkrwE+CCwDzq6qG5Kc2n1+JvBG4JHAXycB2FhVK/vKJEnSJOnznDhVtQZYM2PszGnvXwW8qs8MkiRNKldskySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJapQlLklSoyxxSZIaZYlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVE7Dx1gKR1/wQeGjqCeXPzio4eOIElLzpm4JEmNssQlSWqUJS5JUqMscUmSGmWJS5LUKEtckqRGWeKSJDXKEpckqVGWuCRJjbLEJUlqlCUuSVKjLHFJkhpliUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJapQlLklSo3YeOoAk6YeOv+ADQ0dQTy5+8dHb/DudiUuS1ChLXJKkRlnikiQ1yhKXJKlRlrgkSY2yxCVJapQlLklSoyxxSZIa1WuJJ3lhkhuTrEvy+lk+T5J3dJ9fl+SwPvNIkjRJeivxJMuAdwJHAYcAJyc5ZMZuRwEHda9TgL/pK48kSZOmz5n404B1VXVTVd0PnA8cM2OfY4D31Mingb2TPKrHTJIkTYw+S3w/4NZp2+u7sS3dR5IkzaLPB6BklrFaxD4kOYXR4XaAe5PcuJXZdhT7AncNHWIp5MShE+wQdpifJ/Bnaon4MzW+x8422GeJrwceM217f+C2RexDVZ0FnLWtA066JGurauXQOTQZ/HnStubP1Nbr83D6lcBBSQ5MsgtwErB6xj6rgV/rrlJ/BvCdqvpaj5kkSZoYvc3Eq2pjktcAHwSWAWdX1Q1JTu0+PxNYA/wisA74LrCqrzySJE2aVD3oFLQmRJJTulMR0lbz50nbmj9TW88SlySpUS67KklSoyxxSZIaZYlLkpZMkiOTrOreL09y4NCZWuY58QmT5BGM1qLfbWqsqq4YLpFaluQJjJ59MP3n6T3DJVLLkrwJWAkcXFWPT/Jo4MKqetbA0ZrV52IvWmJJXgWczmjRnGuBZwCfAp43YCw1qvsL9zmMSnwNowcWfRywxLVYxwFPAa4GqKrbkuwxbKS2eTh9spwOHA58taqey+j/LHcOG0kNOwF4PnB7Va0CDgV2HTaSGnd/jQ7/FkCS3QfO0zxLfLLcV1X3ASTZtaq+BBw8cCa163tV9QCwMcmewB3A4wbOpLZdkORvGT2x8tXAh4F3DZypaR5Onyzrk+wNXApcnuRbzLIWvTSmtd3P07uAq4B7gc8OmkhNq6o/T/IC4G7g8cAbq+rygWM1zQvbJlSSZwN7AZd1z3OXFi3JCmDPqrpu6CxqW5IfA57G6JD6lVV1+8CRmubh9AnQHeokyT5TL+B6RhchPXzQcGpWkuOS7AVQVV8Bbkly7KCh1LTu4tvPAsczuubi00leMWyqtjkTnwBJPlBVRye5mdG/bqc/p72qyvOY2mJJrq2qJ88Yu6aqnjJQJDUuyY3AEVX1jW77kcAnq8prdxbJc+IToKqO7n510QRtS7MdqfPvDG2N9cA907bvAW4dKMtEcCY+QZI8C7i2qjYkeSlwGHBGVd0ycDQ1KMnZwLeBdzI6wvNa4BFV9esDxlLDkrwHeCLwPkY/U8cwOrz+ZYCqettw6drkOfHJ8jfAd5McCrwO+Crw98NGUsNeC9wPvBe4ELgP+O1BE6l1/8Ho7pmp2eP7gK8Be3QvbSFn4hMkydVVdViSNwL/WVXvnhobOpskTelWaauqunfoLK3z/NZkuSfJG4CXAT+TZBn+b6wtlOSMqvqdJO/nhzOm/1JVLxogliZAtxb/3wP7dNt3Ab9WVTcMGqxh/gU/WU4EXgKsqqrbk/ws4LKG2lJTp2D+fNAUmkRnAb9XVR8BSPIcRosJHTFgpqZZ4hOkK+5/A16S5B+Am4Ezhk2l1lTVVd1RnFdX1UuHzqOJsvtUgQNU1UddP33rWOITIMnjgZOAk4FvMLoQKd1DUKQtVlWbumc97+KKf9qGbkryR/zwaM9LGU02tEhe2DYBkjwA/Dvwyqpa143d5CIv2hrdgyoOA1YDG6bGvQ1Ii5XkEcCbgSO7oSuAN1fVt4ZL1TZn4pPhlxnNxD+S5DLgfDZftU1ajNu61054+4+2UneK5sKq+rmhs0wSZ+ITpDu3dCyjw+rPA84DLqmqDw2ZS21LsntVbVh4T2l+SVYDL6uq7wydZVJY4hOqewjKrwAnVtXzhs6j9iR5JvBu4OFVdUC3iNBvVNVvDRxNjUpyAfAM4HI2P0Vz2mChGmeJS5pVks8wetLU6qmHniT5fFU9YdhkalWSl882XlXnLXWWSeE5cUlzqqpbk80ur9g0VBa1z7Le9ixxSXO5NckRQCXZBTgN+OLAmdSwaY9L3ox30iyeJS5pLqcCbwf2Y/QIyQ/hA1C0dVZOe78bo+t29hkoy0TwnLgkaTBJPl5VRy68p2bjTFzSrJIcyOhxpCuY9neFD0DRYiWZ/kTFnRjNzF2DYCtY4pLmcimjW8zeDzwwbBRNiL+Y9n4joyVXXzxQlong4XRJs0rymap6+tA5JM1tp6EDSNpuvT3Jm5I8M8lhU6+hQ6k9Sc6Y9v70GZ+du9R5JomH0yXN5YnAyxgt4Tt1OL26bWlL/Oy09y9ndNfDlCctcZaJYolLmstxwON8FKm2gczxXlvJEpc0l88BewN3DJxD7dupewzpTtPeT5X5suFitc8SlzSXHwW+lORK4PtTg95ipkXYC7iKHxb31dM+8+rqreDV6ZJmleTZs41X1ceWOouk2VniksaS5FnAS6rKpVel7YSH0yXNKcmTgZcwWpDjZuCiQQNJ2owlLmkzSR4PnAScDHwDeC+jo3bPHTSYpAfxcLqkzSR5APh34JVVta4bu8nHRWpbSLKM0UWT09fjv2W4RG1zJi5ppl9mNBP/SJLLgPPx3l5tA0leC7wJ+DqbLyDkgi+L5Exc0qyS7A4cy+iw+vOA84BLqupDQ+ZSu5KsA55eVd8YOsuksMQlLSjJPsCvACdWlcuualGSfAR4QVVtHDrLpLDEJUlLIsm7gYOB/8vmCwi9bbBQjfOcuCRpqdzSvXbpXtpKlrgkqXfdVekHVdVLh84ySXyeuCSpd1W1CViexBn4NuRMXNKskhwP/BnwI4xuMQtQVbXnoMHUsq8An0iyGtgwNeg58cWzxCXN5S3AL1XVF4cOoolxW/faCdhj4CwTwavTJc0qySeq6llD59DkSbJ7VW1YeE8txBKXtJnuMDrAs4EfAy5l89uBLh4gliZAkmcC7wYeXlUHJDkU+I2q+q2BozXLEpe0mSTnzPNxVdUrliyMJkqSzwAnAKur6ind2Oer6gnDJmuX58QlbaaqVsHo+eFV9Ynpn3XPFJcWrapuTTZbin/TUFkmgbeYSZrLX445Jo3r1iRHAJVklyS/D3jh5FZwJi5pM915yyMY3dP7e9M+2hNYNkwqTYhTgbcD+wHrgQ8Bng/fCpa4pJl2AR7O6O+H6bcB3c3ofKa0WAdX1a9OH+hO0Xxijv21AC9sk/Qg3RKZ760qS1vbTJKrq+qwhcY0Pmfikh6kqjZ1jx+VtpqnaPpjiUuayzXd8pgXsvkSmd4nri3lKZqeeDhd0qzmuF/c+8S1aEkeW1Vf7d7vxGjRl7sHjtU0S1yStCSS/BOjK9Q3AVcBewFvq6q3DhqsYd4nLmlWSfZPckmSO5J8PclFSfYfOpeadkg38z4WWAMcALxs0ESNs8QlzeUcYDXwaEb39b6/G5MW6yFJHsKoxN9XVT8APBy8FSxxSXNZXlXnVNXG7nUusHzoUGra3zJ6pvjuwBVJHsvo4jYtkufEJc0qyYeBc4F/7oZOBlZV1fMHC6WJk2Tnqto4dI5WOROXNJdXAC8Gbge+xuhWIK9M16Il+dEk707yr932IcDLB47VNGfikqQl0ZX3OcB/r6pDk+wMXFNVTxw4WrNc7EXSZpK8cZ6Pq6r+eMnCaNLsW1UXJHkDQFVtTOKjSLeCJS5ppg2zjO0OvBJ4JGCJa7E2JHkk3RXpSZ4BfGfYSG3zcLqkOSXZAzidUYFfAPxFVd0xbCq1KslTgXcATwA+z+huhxOq6rpBgzXMmbikB+kefvJ7wK8C5wGHVdW3hk2lViX5HUaPG70GeDZwMBDgxu5ecS2SV6dL2kyStwJXAvcAT6yq/2mBayvtD7wduAP4MKN/HD6WzR+GokXwcLqkzSR5APg+sJHNV9MKowvb9hwkmJqXZBdgJaPHkj6ze327qg4ZNFjDPJwuaTNV5RE69eWhjJ4hvlf3ug24ftBEjXMmLknqVZKzgJ9mdIrmM8CngU97mmbr+S9uSVLfDgB2ZbT6338C64FvDxloUjgTlyT1LkkYzcaP6F5PAL4JfKqq3jRktpZZ4pKkJdM9k/5ZjIr8aOCRVbX3oKEaZolLknqV5DRGpf0s4AeM7hn/VPfr9VX1wIDxmubV6ZKkvq0A/gX43ar62sBZJoozcUmSGuXV6ZIkNcoSlySpUZa4NOGS3LuNv+/YJIdM2/5fSX5uW/4ZksbjOXFpwiW5t6oevg2/71zgA1X1L9vqOyUtjjNxaQeRkbcm+XyS65OcOO2z13Vjn0vyp93Yq5Nc2Y1dlORhSY4AXgS8Ncm1SX48yblJTuh+z/OTXNN919lJdu3Gv5LkzUmu7j77ySH+O5AmjSUu7TiOB54MHAr8HKMiflSSo4BjgadX1aHAW7r9L66qw7uxLwKvrKpPAquBP6iqJ1fVf0x9eZLdgHOBE6vqiYxuYf3NaX/+XVV1GPA3wO/39x9T2nFY4tKO40jgn6tqU1V9HfgYcDijQj+nqr4LUFXf7PZ/QpJ/T3I9o+c///QC338wcHNVfbnbPg/42WmfX9z9ehWj+4YlbSVLXNpxZJ7x2S6OORd4TTerfjOw2yK/f8r3u1834UJT0jZhiUs7jiuAE5MsS7Kc0Sz5s8CHgFckeRhAkn26/fcAvpbkIYxm4lPu6T6b6UvAiiQ/0W2/jNFsX1JPLHFpx3EJcB3wOeDfgNdV1e1VdRmj89xrk1zLD89X/xGjZz9fzqigp5wP/EF3AduPTw1W1X3AKuDC7hD8A8CZ/f5HknZs3mImSVKjnIlLktQoS1ySpEZZ4pIkNcoSlySpUZa4JEmNssQlSWqUJS5JUqMscUmSGvX/AVE6o+/2DIZPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Where are you geographically located?\")\n",
    "make_plot_categorical(selectedParticipants, 'location')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In terms of racial or ethnic identity, do you consider yourself a minority with respect to the field of geospatial science?\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"In terms of racial or ethnic identity, do you consider yourself a minority with respect to the field of geospatial science?\")\n",
    "make_plot_categorical(selectedParticipants, 'In terms of racial or ethnic identity, do you consider yourself a minority with respect to the field of geospatial science?')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In terms of gender identity, do you consider yourself a minority with respect to the field of geospatial science?\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"In terms of gender identity, do you consider yourself a minority with respect to the field of geospatial science?\")\n",
    "make_plot_categorical(selectedParticipants, 'In terms of gender identity, do you consider yourself a minority with respect to the field of geospatial science?')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:hackweek-admin]",
   "language": "python",
   "name": "conda-env-hackweek-admin-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}