Lab.ipynb

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   "id": "9522d662-2593-4a6a-b39b-7abd2e4e8be6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas\n",
    "import pandas\n",
    "import shapely"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d8430fd5-56d4-47b6-b763-836636e219f0",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>url</th>\n",
       "      <th>line</th>\n",
       "      <th>notes</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>objectid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Astor Pl</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>4-6-6 Express</td>\n",
       "      <td>4 nights, 6-all times, 6 Express-weekdays AM s...</td>\n",
       "      <td>POINT (-73.99107 40.73005)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Canal St</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>4-6-6 Express</td>\n",
       "      <td>4 nights, 6-all times, 6 Express-weekdays AM s...</td>\n",
       "      <td>POINT (-74.00019 40.71880)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50th St</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>1-2</td>\n",
       "      <td>1-all times, 2-nights</td>\n",
       "      <td>POINT (-73.98385 40.76173)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bergen St</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>2-3-4</td>\n",
       "      <td>4-nights, 3-all other times, 2-all times</td>\n",
       "      <td>POINT (-73.97500 40.68086)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Pennsylvania Ave</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>3-4</td>\n",
       "      <td>4-nights, 3-all other times</td>\n",
       "      <td>POINT (-73.89489 40.66471)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>469</th>\n",
       "      <td>Coney Island - Stillwell Av</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>D-F-N-Q</td>\n",
       "      <td>D,F,N,Q-all times</td>\n",
       "      <td>POINT (-73.98124 40.57728)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>34th St - Hudson Yards</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>7-7 Express</td>\n",
       "      <td>7-all times, 7 Express-rush hours AM westbound...</td>\n",
       "      <td>POINT (-74.00220 40.75545)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>641</th>\n",
       "      <td>72nd St</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>Q</td>\n",
       "      <td>Q-all times</td>\n",
       "      <td>POINT (-73.95836 40.76880)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>642</th>\n",
       "      <td>86th St</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>Q</td>\n",
       "      <td>Q-all times</td>\n",
       "      <td>POINT (-73.95177 40.77786)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>643</th>\n",
       "      <td>96th St</td>\n",
       "      <td>http://web.mta.info/nyct/service/</td>\n",
       "      <td>Q</td>\n",
       "      <td>Q-all times</td>\n",
       "      <td>POINT (-73.94707 40.78424)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>473 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 name                                url  \\\n",
       "objectid                                                                   \n",
       "1                            Astor Pl  http://web.mta.info/nyct/service/   \n",
       "2                            Canal St  http://web.mta.info/nyct/service/   \n",
       "3                             50th St  http://web.mta.info/nyct/service/   \n",
       "4                           Bergen St  http://web.mta.info/nyct/service/   \n",
       "5                    Pennsylvania Ave  http://web.mta.info/nyct/service/   \n",
       "...                               ...                                ...   \n",
       "469       Coney Island - Stillwell Av  http://web.mta.info/nyct/service/   \n",
       "470            34th St - Hudson Yards  http://web.mta.info/nyct/service/   \n",
       "641                           72nd St  http://web.mta.info/nyct/service/   \n",
       "642                           86th St  http://web.mta.info/nyct/service/   \n",
       "643                           96th St  http://web.mta.info/nyct/service/   \n",
       "\n",
       "                   line                                              notes  \\\n",
       "objectid                                                                     \n",
       "1         4-6-6 Express  4 nights, 6-all times, 6 Express-weekdays AM s...   \n",
       "2         4-6-6 Express  4 nights, 6-all times, 6 Express-weekdays AM s...   \n",
       "3                   1-2                              1-all times, 2-nights   \n",
       "4                 2-3-4           4-nights, 3-all other times, 2-all times   \n",
       "5                   3-4                        4-nights, 3-all other times   \n",
       "...                 ...                                                ...   \n",
       "469             D-F-N-Q                                  D,F,N,Q-all times   \n",
       "470         7-7 Express  7-all times, 7 Express-rush hours AM westbound...   \n",
       "641                   Q                                        Q-all times   \n",
       "642                   Q                                        Q-all times   \n",
       "643                   Q                                        Q-all times   \n",
       "\n",
       "                            geometry  \n",
       "objectid                              \n",
       "1         POINT (-73.99107 40.73005)  \n",
       "2         POINT (-74.00019 40.71880)  \n",
       "3         POINT (-73.98385 40.76173)  \n",
       "4         POINT (-73.97500 40.68086)  \n",
       "5         POINT (-73.89489 40.66471)  \n",
       "...                              ...  \n",
       "469       POINT (-73.98124 40.57728)  \n",
       "470       POINT (-74.00220 40.75545)  \n",
       "641       POINT (-73.95836 40.76880)  \n",
       "642       POINT (-73.95177 40.77786)  \n",
       "643       POINT (-73.94707 40.78424)  \n",
       "\n",
       "[473 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stations = geopandas.read_file(\"Subway Stations.geojson\")\n",
    "stations.set_index('objectid', inplace=True)\n",
    "stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "07f66b59-36cd-4de1-8584-75ddbe07067f",
   "metadata": {},
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    {
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       "            geo_json_95cccd34ebe35e41af4205644da2ff89_add({&quot;bbox&quot;: [-74.03087600085765, 40.576033818103646, -73.75540499924732, 40.903125000541245], &quot;features&quot;: [{&quot;bbox&quot;: [-73.99106999861966, 40.73005400028978, -73.99106999861966, 40.73005400028978], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.99106999861966, 40.73005400028978], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;4-6-6 Express&quot;, &quot;name&quot;: &quot;Astor Pl&quot;, &quot;notes&quot;: &quot;4 nights, 6-all times, 6 Express-weekdays AM southbound, PM northbound&quot;, &quot;objectid&quot;: &quot;1&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-74.00019299927328, 40.71880300107709, -74.00019299927328, 40.71880300107709], &quot;geometry&quot;: {&quot;coordinates&quot;: [-74.00019299927328, 40.71880300107709], 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{&quot;line&quot;: &quot;4-6-6 Express&quot;, &quot;name&quot;: &quot;Bleecker St&quot;, &quot;notes&quot;: &quot;4 nights, 6-all times, 6 Express-weekdays PM&quot;, &quot;objectid&quot;: &quot;457&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.94747800152219, 40.79060000008452, -73.94747800152219, 40.79060000008452], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.94747800152219, 40.79060000008452], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;457&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;4-6-6 Express&quot;, &quot;name&quot;: &quot;103rd St&quot;, &quot;notes&quot;: &quot;4 nights, 6-all times, 6 Express-weekdays AM southbound, PM northbound&quot;, &quot;objectid&quot;: &quot;458&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.87210600099675, 40.675376998239365, 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&quot;objectid&quot;: &quot;460&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.96379005505493, 40.6409401651401, -73.96379005505493, 40.6409401651401], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.96379005505493, 40.6409401651401], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;460&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;Q&quot;, &quot;name&quot;: &quot;Cortelyou Rd&quot;, &quot;notes&quot;: &quot;Q-all times&quot;, &quot;objectid&quot;: &quot;461&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.9416169983714, 40.7986290002001, -73.9416169983714, 40.7986290002001], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.9416169983714, 40.7986290002001], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;461&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;4-6-6 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40.719318001302135], &quot;geometry&quot;: {&quot;coordinates&quot;: [-74.00688600277107, 40.719318001302135], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;463&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;1-2&quot;, &quot;name&quot;: &quot;Franklin St&quot;, &quot;notes&quot;: &quot;1-all times, 2-nights&quot;, &quot;objectid&quot;: &quot;464&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.85899200206335, 40.67937100115432, -73.85899200206335, 40.67937100115432], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.85899200206335, 40.67937100115432], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;464&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;A-S&quot;, &quot;name&quot;: &quot;80th St&quot;, &quot;notes&quot;: &quot;A-all times, S Euclid Av to Ozone Park-Lefferts Blvd-nights&quot;, &quot;objectid&quot;: &quot;465&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.98196299856706, 40.75382100064824, -73.98196299856706, 40.75382100064824], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.98196299856706, 40.75382100064824], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;465&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;7-7 Express&quot;, &quot;name&quot;: &quot;5th Ave - Bryant Pk&quot;, &quot;notes&quot;: &quot;7-all times, 7 Express-rush hours AM westbound, PM eastbound&quot;, &quot;objectid&quot;: &quot;466&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.99714100006673, 40.72230099999366, -73.99714100006673, 40.72230099999366], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.99714100006673, 40.72230099999366], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;466&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;4-6-6 Express&quot;, &quot;name&quot;: &quot;Spring St&quot;, &quot;notes&quot;: &quot;4 nights, 6-all times, 6 Express-weekdays AM southbound, PM northbound&quot;, &quot;objectid&quot;: &quot;467&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.93759400055725, 40.804138000587244, -73.93759400055725, 40.804138000587244], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.93759400055725, 40.804138000587244], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;467&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;4-5-6-6 Express&quot;, &quot;name&quot;: &quot;125th St&quot;, &quot;notes&quot;: &quot;4,6-all times, 5-all times exc nights, 6 Express-weekdays AM southbound, PM northbound&quot;, &quot;objectid&quot;: &quot;468&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.9812359981396, 40.57728100006751, -73.9812359981396, 40.57728100006751], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.9812359981396, 40.57728100006751], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;468&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;D-F-N-Q&quot;, &quot;name&quot;: &quot;Coney Island - Stillwell Av&quot;, &quot;notes&quot;: &quot;D,F,N,Q-all times&quot;, &quot;objectid&quot;: &quot;469&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-74.00219709442206, 40.75544635961596, -74.00219709442206, 40.75544635961596], &quot;geometry&quot;: {&quot;coordinates&quot;: [-74.00219709442206, 40.75544635961596], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;469&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;7-7 Express&quot;, &quot;name&quot;: &quot;34th St - Hudson Yards&quot;, &quot;notes&quot;: &quot;7-all times, 7 Express-rush hours AM westbound, PM eastbound&quot;, &quot;objectid&quot;: &quot;470&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.95836178682246, 40.76880251014895, -73.95836178682246, 40.76880251014895], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.95836178682246, 40.76880251014895], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;470&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;Q&quot;, &quot;name&quot;: &quot;72nd St&quot;, &quot;notes&quot;: &quot;Q-all times&quot;, &quot;objectid&quot;: &quot;641&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.95177090964917, 40.77786104333163, -73.95177090964917, 40.77786104333163], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.95177090964917, 40.77786104333163], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;471&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;Q&quot;, &quot;name&quot;: &quot;86th St&quot;, &quot;notes&quot;: &quot;Q-all times&quot;, &quot;objectid&quot;: &quot;642&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.9470660219183, 40.784236650177654, -73.9470660219183, 40.784236650177654], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.9470660219183, 40.784236650177654], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;472&quot;, &quot;properties&quot;: {&quot;line&quot;: &quot;Q&quot;, &quot;name&quot;: &quot;96th St&quot;, &quot;notes&quot;: &quot;Q-all times&quot;, &quot;objectid&quot;: &quot;643&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_95cccd34ebe35e41af4205644da2ff89.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;objectid&quot;, &quot;name&quot;, &quot;url&quot;, &quot;line&quot;, &quot;notes&quot;];\n",
       "    let aliases = [&quot;objectid&quot;, &quot;name&quot;, &quot;url&quot;, &quot;line&quot;, &quot;notes&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
       "                     \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x13ef01450>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stations.explore()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "42394308-a274-478f-9174-b0c242752549",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23/473\n"
     ]
    },
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42nd St&quot;, &quot;notes&quot;: &quot;7-all times, 7 Express-rush hours AM westbound, PM eastbound&quot;, &quot;objectid&quot;: &quot;204&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.90428999746412, 40.67936600147369, -73.90428999746412, 40.67936600147369], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.90428999746412, 40.67936600147369], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;12&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;J-Z&quot;, &quot;name&quot;: &quot;Broadway Junction&quot;, &quot;notes&quot;: &quot;J-all times, Z-rush hours AM westbound, PM eastbound&quot;, &quot;objectid&quot;: &quot;224&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.91217899939602, 40.69945400090837, -73.91217899939602, 40.69945400090837], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.91217899939602, 40.69945400090837], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;13&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;M&quot;, &quot;name&quot;: &quot;Myrtle - Wyckoff Aves&quot;, &quot;notes&quot;: &quot;M-all times&quot;, &quot;objectid&quot;: &quot;233&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.95582700110425, 40.68059566598263, -73.95582700110425, 40.68059566598263], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.95582700110425, 40.68059566598263], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;14&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;S&quot;, &quot;name&quot;: &quot;Franklin Ave - Fulton St&quot;, &quot;notes&quot;: &quot;S to Prospect Park-all times&quot;, &quot;objectid&quot;: &quot;288&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.98749500051885, 40.75528999995681, -73.98749500051885, 40.75528999995681], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.98749500051885, 40.75528999995681], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;15&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;1-2-3&quot;, &quot;name&quot;: &quot;Times Sq - 42nd St&quot;, &quot;notes&quot;: &quot;1,2,3-all times&quot;, &quot;objectid&quot;: &quot;359&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.98605667854612, 40.69225539645323, -73.98605667854612, 40.69225539645323], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.98605667854612, 40.69225539645323], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;16&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;N-R&quot;, &quot;name&quot;: &quot;Jay St - MetroTech&quot;, &quot;notes&quot;: &quot;N-nights, R-all other times&quot;, &quot;objectid&quot;: &quot;377&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.99053886181645, 40.73587226699812, -73.99053886181645, 40.73587226699812], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.99053886181645, 40.73587226699812], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;17&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;N-Q-R-W&quot;, &quot;name&quot;: &quot;Union Sq - 14th St&quot;, &quot;notes&quot;: &quot;N,Q-all times, R-all times exc nights&quot;, &quot;objectid&quot;: &quot;379&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.90531600055341, 40.67833366608023, -73.90531600055341, 40.67833366608023], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.90531600055341, 40.67833366608023], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;18&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;A-C&quot;, &quot;name&quot;: &quot;Broadway Junction&quot;, &quot;notes&quot;: &quot;A-all times, C-all times exc nights&quot;, &quot;objectid&quot;: &quot;386&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.98999799960687, 40.693218999611084, -73.98999799960687, 40.693218999611084], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.98999799960687, 40.693218999611084], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;19&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;2-3&quot;, &quot;name&quot;: &quot;Borough Hall&quot;, &quot;notes&quot;: &quot;2-all times, 3-all times exc nights&quot;, &quot;objectid&quot;: &quot;406&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-74.00105471306033, 40.718814263587134, -74.00105471306033, 40.718814263587134], &quot;geometry&quot;: {&quot;coordinates&quot;: [-74.00105471306033, 40.718814263587134], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;20&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;N-Q&quot;, &quot;name&quot;: &quot;Canal St&quot;, &quot;notes&quot;: &quot;N-all times, Q-weekdays and evenings&quot;, &quot;objectid&quot;: &quot;435&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-73.99620899921355, 40.73822799969515, -73.99620899921355, 40.73822799969515], &quot;geometry&quot;: {&quot;coordinates&quot;: [-73.99620899921355, 40.73822799969515], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;21&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;F-M&quot;, &quot;name&quot;: &quot;14th St&quot;, &quot;notes&quot;: &quot;F-all times, M-weekdays and evenings&quot;, &quot;objectid&quot;: &quot;441&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [-74.00168999937027, 40.740893000193296, -74.00168999937027, 40.740893000193296], &quot;geometry&quot;: {&quot;coordinates&quot;: [-74.00168999937027, 40.740893000193296], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;22&quot;, &quot;properties&quot;: {&quot;labeled&quot;: null, &quot;line&quot;: &quot;A-C-E&quot;, &quot;name&quot;: &quot;14th St&quot;, &quot;notes&quot;: &quot;A,E-all times, C-all times exc nights&quot;, &quot;objectid&quot;: &quot;444&quot;, &quot;url&quot;: &quot;http://web.mta.info/nyct/service/&quot;}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
       "\n",
       "        \n",
       "    \n",
       "    geo_json_c543fba9254c5f68748ac4c5a8473ec7.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;objectid&quot;, &quot;name&quot;, &quot;line&quot;];\n",
       "    let aliases = [&quot;objectid&quot;, &quot;name&quot;, &quot;line&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
       "                     \n",
       "    \n",
       "    geo_json_c543fba9254c5f68748ac4c5a8473ec7.bindPopup(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;objectid&quot;, &quot;name&quot;, &quot;line&quot;];\n",
       "    let aliases = [&quot;objectid&quot;, &quot;name&quot;, &quot;line&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i].toLocaleString()}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v]).toLocaleString()}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumpopup&quot;});\n",
       "                     \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2a007c310>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xml.etree import ElementTree\n",
    "from svgpathtools import parse_path\n",
    "from svgpathtools.path import transform\n",
    "import numpy as np\n",
    "import re\n",
    "FLOAT_RE = r\"([-+]?\\d+(?:\\.\\d+)?)\"\n",
    "MATRIX_RE = re.compile(r\"matrix\\s*\\(\\s*\" + r\"\\s*,\\s*\".join((FLOAT_RE,) * 6) + r\"\\s*\\)\")\n",
    "subway_map_tree = ElementTree.parse(\"subway_map_annotated.svg\")\n",
    "subway_map_root = subway_map_tree.getroot()\n",
    "_, _, subway_map_width, subway_map_height = (int(s) for s in subway_map_root.get('viewBox').split())\n",
    "\n",
    "stations['labeled'] = None\n",
    "for elem in subway_map_root.iter('{http://www.w3.org/2000/svg}g'):\n",
    "    if (name := elem.get('id')) is None or not name.startswith('station-'):\n",
    "        continue\n",
    "    good_elem = elem\n",
    "    station_id = name[8:]\n",
    "    a, b, c, d, e, f = (float(x) for x in MATRIX_RE.match(elem.get('transform')).groups())\n",
    "    #stations.at[station_id, 'labeled'] = shapely.Point(e, -f)\n",
    "    transform_matrix = np.array([[a, c, e], [b, d, f], [0, 0, 1]])\n",
    "    path = transform(parse_path(elem[0].get('d')), transform_matrix)\n",
    "    xmin, xmax, ymin, ymax = path.bbox()\n",
    "    if stations.at[station_id, 'labeled'] is not None:\n",
    "        raise ValueError(f\"saw station #{station_id} more than once??\")\n",
    "    stations.at[station_id, 'labeled'] = shapely.Point((xmax + xmin) / 2, -(ymax + ymin) / 2)\n",
    "\n",
    "unlabeled_stations = stations[stations['labeled'].isnull()]\n",
    "print(f\"{len(unlabeled_stations)}/{len(stations)}\")\n",
    "unlabeled_stations.explore(marker_kwds={'radius': 5}, tooltip=('objectid', 'name', 'line'), popup=('objectid', 'name', 'line'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c8ede9a1-e0de-4b68-a6da-d2f60c43bf76",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1922, 2323)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subway_map_width, subway_map_height"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e12aa758-e322-46a3-9390-7bbc8bbc54a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jessie/Library/Python/3.11/lib/python/site-packages/geopandas/plotting.py:732: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(values.dtype):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labeled_stations = stations[~stations['labeled'].isnull()]\n",
    "labeled_stations.plot('line')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a3d1edb7-cce9-4d28-8c40-8acae14622ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jessie/Library/Python/3.11/lib/python/site-packages/geopandas/plotting.py:732: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(values.dtype):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labeled_stations_mapped = labeled_stations.set_geometry('labeled')\n",
    "labeled_stations_mapped.plot('line')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e94d3f22-863e-40bf-9be1-8461b196a7b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-74.14734350787045, 40.442928582900024, -73.60065607717453, 41.01516226647475)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import geodatasets\n",
    "\n",
    "boros = geopandas.read_file(geodatasets.get_path(\"nybb\")).to_crs(stations.crs)\n",
    "real_boros = boros[boros['BoroName'] != 'Staten Island']\n",
    "nyc_outline = real_boros['geometry'].unary_union.convex_hull.buffer(0.1, quad_segs=4)\n",
    "nyc_outline.bounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "67913ce2-21f9-4b25-aece-2511f691aaae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "142.0 -2162.579345709999 1858.0699999999997 -61.64504255499999\n",
      "0 -2122.5 1922 -200.5\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "def normalize(min_, max_, x):\n",
    "    return (x - min_) / (max_ - min_)\n",
    "def squarify(minx, miny, maxx, maxy):\n",
    "    rangex = maxx - minx\n",
    "    rangey = maxy - miny\n",
    "    diff = abs(rangex - rangey)\n",
    "    if rangey > rangex:\n",
    "        return minx - diff/2, miny, maxx + diff/2, maxy\n",
    "    else:\n",
    "        return minx, miny - diff/2, maxx, maxy + diff/2\n",
    "def browser_data(stations):\n",
    "    point_to_idx = {(pt.x, pt.y): i for i, pt in enumerate(stations['geometry'])}\n",
    "    station_mp = shapely.MultiPoint(stations['geometry'].array)\n",
    "    print(*shapely.MultiPoint(stations['labeled'].array).bounds)\n",
    "    minx, miny, maxx, maxy = squarify(*shapely.MultiPoint(stations['labeled'].array).bounds)\n",
    "    minx, miny, maxx, maxy = squarify(0, 0, subway_map_width, -subway_map_height)\n",
    "    print(minx, miny, maxx, maxy)\n",
    "    tris = shapely.delaunay_triangles(station_mp)\n",
    "    return {\n",
    "        'input_crs': stations.crs.name,\n",
    "        'vertices': [\n",
    "            (st['geometry'].x,\n",
    "             st['geometry'].y,\n",
    "             normalize(minx, maxx, st['labeled'].x),\n",
    "             normalize(miny, maxy, st['labeled'].y))\n",
    "            for _, st\n",
    "            in stations.iterrows()\n",
    "        ],\n",
    "        'triangles': [[point_to_idx[pt] for pt in list(poly.exterior.coords)[:-1]] for poly in tris.geoms]\n",
    "    }\n",
    "spec = browser_data(labeled_stations)\n",
    "with open(\"data.json\", 'w') as f:\n",
    "    json.dump(spec, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "48a0183a-093b-445a-b7ce-115ec0a24964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(142.0, -2162.579345709999, 1858.0699999999997, -61.64504255499999)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shapely.MultiPoint(labeled_stations['labeled'].array).bounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "4eb555e1-2928-44c7-bf90-bf6b69143ff6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(-73.72812100059289, 40.727904998845844),\n",
       " (-73.72812100059289, 40.819644999410976),\n",
       " (-73.72812100059289, 40.911384999976114),\n",
       " (-73.72812100059289, 41.003125000541246),\n",
       " (-73.8061240002128, 41.003125000541246),\n",
       " (-73.88412699983273, 41.003125000541246),\n",
       " (-73.96212999945266, 41.003125000541246),\n",
       " (-74.04013299907257, 41.003125000541246),\n",
       " (-74.04013299907257, 40.911384999976114),\n",
       " (-74.04013299907257, 40.819644999410976),\n",
       " (-74.04013299907257, 40.727904998845844),\n",
       " (-73.96212999945266, 40.727904998845844),\n",
       " (-73.88412699983273, 40.727904998845844),\n",
       " (-73.8061240002128, 40.727904998845844),\n",
       " (-73.72812100059289, 40.727904998845844)]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_mp = shapely.MultiPoint(labeled_stations['geometry'].array)\n",
    "buffered = station_mp.buffer(0.1)\n",
    "bounds = shapely.geometry.box(*buffered.bounds)\n",
    "denser = bounds.segmentize(0.1)\n",
    "list(denser.exterior.coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4db73d53-29f5-46ec-8ec1-2ab8d25787ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "[1, 2, 3, 4][:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "82f228f6-9409-4af2-877b-5e65d389732b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyproj\n",
    "mta_trans = pyproj.Transformer.from_pipeline(mta_crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7a20c090-e30d-4319-825e-2f06a7543b55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mta_trans.has_inverse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ad8aa4e7-4e45-4dfa-97e4-e09409d648e6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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