example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "hmd100 = heatmap.preprocess.HeatmapData(assignment_id=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sections_to_preceptor = {\n",
    "    \"P01\": \"Ellen\",\n",
    "    \"P02\": \"Sylvia\",\n",
    "    \"P03\": \"Justin\",\n",
    "    \"P04\": \"Jacob\",\n",
    "    \"P05\": \"Andrew\",\n",
    "    \"P06\": \"Josh\",\n",
    "    \"P07\": \"Robert\",\n",
    "    \"P07A\": \"Sylvia\",\n",
    "    \"P10\": \"Phillip\",\n",
    "    \"P10A\": \"Robert\",\n",
    "    \"P11\": \"Ellen\",\n",
    "    \"P11A\": \"Josh\",\n",
    "    \"P12\": \"Dante\",\n",
    "    \"P13\": \"Dante\",\n",
    "    \"P14\": \"Phillip\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "heatmap100 = heatmap.draw.build_heatmap(hmd100,\n",
    "                                        x=heatmap.draw.HeatmapXAxis.TEACHERS,\n",
    "                                        y=heatmap.draw.HeatmapYAxis.CATEGORIES,\n",
    "                                        section_to_teacher=sections_to_preceptor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1490.4x1099.44 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "heatmap.draw.render_heatmap_data(heatmap100, x_caption=\"Teachers\", y_caption=\"Categories\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}