nb_005_Ames1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "negative-estate",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas\n",
    "school_dists = geopandas.read_file('data/geo/ames_school_districts.geojson')\n",
    "school_dists['color'] = ['#00b2fd', '#A1A600', '#00C377', '#F95DFA', '#FF6C67']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "august-sympathy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "school_dists.plot(figsize=(15,15), color = school_dists['color'], edgecolor=\"black\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aerial-commitment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>district</th>\n",
       "      <th>fill_color</th>\n",
       "      <th>geometry</th>\n",
       "      <th>color</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mitchell Elementary School</td>\n",
       "      <td>#bee2efff</td>\n",
       "      <td>MULTIPOLYGON (((-93.58127 42.04173, -93.58127 ...</td>\n",
       "      <td>#00b2fd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Fellows Elementary School</td>\n",
       "      <td>#bce4bd</td>\n",
       "      <td>MULTIPOLYGON (((-93.65905 42.05743, -93.65905 ...</td>\n",
       "      <td>#A1A600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Meeker Elementary School</td>\n",
       "      <td>#f7cb96</td>\n",
       "      <td>MULTIPOLYGON (((-93.64100 42.04539, -93.64100 ...</td>\n",
       "      <td>#00C377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sawyer Elementary School</td>\n",
       "      <td>#f8cfda</td>\n",
       "      <td>MULTIPOLYGON (((-93.64473 42.04238, -93.64473 ...</td>\n",
       "      <td>#F95DFA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Edwards Elementary School</td>\n",
       "      <td>#fcf9c6</td>\n",
       "      <td>MULTIPOLYGON (((-93.66566 42.03080, -93.66566 ...</td>\n",
       "      <td>#FF6C67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     district fill_color  \\\n",
       "0  Mitchell Elementary School  #bee2efff   \n",
       "1   Fellows Elementary School    #bce4bd   \n",
       "2    Meeker Elementary School    #f7cb96   \n",
       "3    Sawyer Elementary School    #f8cfda   \n",
       "4   Edwards Elementary School    #fcf9c6   \n",
       "\n",
       "                                            geometry    color  \n",
       "0  MULTIPOLYGON (((-93.58127 42.04173, -93.58127 ...  #00b2fd  \n",
       "1  MULTIPOLYGON (((-93.65905 42.05743, -93.65905 ...  #A1A600  \n",
       "2  MULTIPOLYGON (((-93.64100 42.04539, -93.64100 ...  #00C377  \n",
       "3  MULTIPOLYGON (((-93.64473 42.04238, -93.64473 ...  #F95DFA  \n",
       "4  MULTIPOLYGON (((-93.66566 42.03080, -93.66566 ...  #FF6C67  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_dists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "guided-novelty",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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