{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "db6b54c7-4b0f-46ef-b3d5-29a433e7661e",
   "metadata": {},
   "source": [
    "#### This project aims to conduct an analysis of heatwave patterns across the Chicago over the past lustrum (2020.10.1-2025.10.1). The research will focus on identifying spatial variations and intensity patterns of heatwave events using CyberGISX. The ultimate goal is to create interactive visualizations that effectively communicate heat risk patterns to support urban planning and public health preparedness."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fab21a31-bbb6-4850-ae81-42b943d16258",
   "metadata": {},
   "source": [
    "#### The primary data will be sourced from the National Oceanic and Atmospheric Administration (NOAA) through its Global Historical Climatology Network (GHCN). I use daily maximum temperature collected by different stations as the main variable to analyze."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "425b03f7-35ff-45a6-a5c0-dfc806ec0799",
   "metadata": {},
   "source": [
    "#### Due to the restrictions of the data resources on the size of the dataset, I will make multiple requests for data and combine the datasets from the same observation station into one before conducting further analysis. I will use the geospatial tools including folium, matplotlib, pandas and geopandas to conduct further analysis and comparison of different observation stations, and finally visualize the patterns and intensities of heat waves."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1aa43a0d-c01b-437d-bfed-463fc947694e",
   "metadata": {},
   "source": [
    "#### For now, I just request the data once from NOAA, and I can get the data of 2 years, from 2023.9.1 to 2025.9.1. I select one station to give an example of what I would do. I use 90°F as a heatwave threshold and draw a graph of daily maximum temperature. Also, I draw the map of Chicago using Folium."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "40e7faa9-e850-43d4-803b-333c0a7bf3bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import folium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0e3d920d-8490-4f13-90ef-8f611fe878c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('weather_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a652684d-d7ee-4c33-ad9d-75add6443024",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_clean = df[df.STATION == \"USC00111577\"].reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8a20dae9-9f4b-4169-917b-4fa81ed1f40c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x600 with 0 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "76d94918-cffb-41c6-8ddb-e1e16af541b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_clean.index, df_clean['TMAX'], 'b-', linewidth=1.0, alpha=0.8, label='Daily Max Temperature (°F)')\n",
    "plt.axhline(y=90, color='red', linestyle='--', linewidth=2, alpha=0.8, label='Heatwave Threshold (90°F)')\n",
    "plt.xlabel('Days from 2023.9.1')\n",
    "plt.ylabel('Temperature (°F)')\n",
    "plt.title('Maximum Temperature (TMAX) with Heatwave Threshold in Chicago')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6617d30c-0e29-40ac-901d-ccb4eac05cf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_chicago():\n",
    "    chicago_center = [41.8781, -87.6298]\n",
    "    m = folium.Map(location=chicago_center, zoom_start=10, tiles='OpenStreetMap')\n",
    "    folium.Marker(\n",
    "        chicago_center,\n",
    "        popup='Chicago Downtown',\n",
    "        tooltip='Click for more info',\n",
    "        icon=folium.Icon(color='red', icon='info-sign')\n",
    "    ).add_to(m)\n",
    "    return m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "eeeca797-4911-46fa-9c6a-5615d61f77a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;html&gt;\n",
       "&lt;head&gt;\n",
       "    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_e479f7115a97ee5c44060c3acff97130 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_e479f7115a97ee5c44060c3acff97130&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_e479f7115a97ee5c44060c3acff97130 = L.map(\n",
       "                &quot;map_e479f7115a97ee5c44060c3acff97130&quot;,\n",
       "                {\n",
       "                    center: [41.8781, -87.6298],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 10,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_8b01ea3b0487053347458b2fc8ab6e54 = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_e479f7115a97ee5c44060c3acff97130);\n",
       "        \n",
       "    \n",
       "            var marker_abb40639c31f6457803f24ad99535371 = L.marker(\n",
       "                [41.8781, -87.6298],\n",
       "                {}\n",
       "            ).addTo(map_e479f7115a97ee5c44060c3acff97130);\n",
       "        \n",
       "    \n",
       "            var icon_3eb1ebe7c17be75043ba3cab2529efb9 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;info-sign&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;red&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_abb40639c31f6457803f24ad99535371.setIcon(icon_3eb1ebe7c17be75043ba3cab2529efb9);\n",
       "        \n",
       "    \n",
       "        var popup_52ce63ae73c5c2915bd673633537b0a0 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_0325da295bab1b817de134668a51afa3 = $(`&lt;div id=&quot;html_0325da295bab1b817de134668a51afa3&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Chicago Downtown&lt;/div&gt;`)[0];\n",
       "                popup_52ce63ae73c5c2915bd673633537b0a0.setContent(html_0325da295bab1b817de134668a51afa3);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_abb40639c31f6457803f24ad99535371.bindPopup(popup_52ce63ae73c5c2915bd673633537b0a0)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            marker_abb40639c31f6457803f24ad99535371.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     Click for more info\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\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 0x7fe2c5d87b80>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_chicago()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff64cc36-a564-4af0-aae5-5953f68c5b4f",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### After deciding the variables and scope to focus on, now it is time to calculate the heatwave frequency. As I mentioned, I choose 90°F as a heatwave threshold. If the maximum temperature exceed 90°F for more 2 consecutive days, these days will be considered as having a heatwave. Since I can only get the data of maximuim temperature for 2 years at a time, I respectively request the data of 2020-2021, 2021-2023, and 2023-2025. Then I write a function to calculate the number of heatwave days of the each stations with effective data and record the result, presenting below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a7f7f310-86c4-4cca-b0c2-73c8f68960e2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       STATION  NumDays\n",
      "0  USC00111550        2\n",
      "1  USC00111577       18\n",
      "2  USC00115097        7\n",
      "3  USC00115110        0\n",
      "4  USC00116616        7\n",
      "5  USC00117457        4\n",
      "6  USW00004838       16\n",
      "7  USW00014819       18\n",
      "8  USW00094846       10\n"
     ]
    }
   ],
   "source": [
    "df_01 = pd.read_csv('Tmax01.csv', na_values = [\"NaN\"])\n",
    "df_01_clean = df_01.dropna()\n",
    "df_01_clean.reset_index()\n",
    "df_01_clean.NAME.unique()\n",
    "df_01_s = df_01_clean.sort_values([\"STATION\", \"DATE\"]).reset_index(drop=True)\n",
    "def count_hot_days(sub_df):\n",
    "    temps = sub_df[\"TMAX\"]\n",
    "    mask = temps > 90\n",
    "    groups = (mask != mask.shift()).cumsum()\n",
    "    streak_lengths = mask.groupby(groups).sum()\n",
    "    valid_groups = streak_lengths[streak_lengths >= 2].index\n",
    "    total_days = mask.groupby(groups).sum().loc[valid_groups].sum()\n",
    "    return total_days\n",
    "result_01 = df_01_s.groupby(\"STATION\").apply(count_hot_days).reset_index(name=\"NumDays\")\n",
    "print(result_01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "eb5710e3-84ae-4fd5-ab08-7153a0ba256c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       STATION  NumDays\n",
      "0  USC00111550        5\n",
      "1  USC00111577       30\n",
      "2  USC00115097       11\n",
      "3  USC00116616       14\n",
      "4  USC00117457       12\n",
      "5  USW00004838       15\n",
      "6  USW00014819       30\n",
      "7  USW00094846       20\n"
     ]
    }
   ],
   "source": [
    "df_13 = pd.read_csv('Tmax13.csv', na_values = [\"NaN\"])\n",
    "df_13_clean = df_13.dropna()\n",
    "df_13_clean.reset_index()\n",
    "df_13_clean.NAME.unique()\n",
    "df_13_s = df_13_clean.sort_values([\"STATION\", \"DATE\"]).reset_index(drop=True)\n",
    "result_13 = df_13_s.groupby(\"STATION\").apply(count_hot_days).reset_index(name=\"NumDays\")\n",
    "print(result_13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "dc2a16f4-f639-45a1-9928-5e2875d776f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       STATION  NumDays\n",
      "0  USC00111550       13\n",
      "1  USC00111577       38\n",
      "2  USC00115097       14\n",
      "3  USC00116616       22\n",
      "4  USC00117457       21\n",
      "5  USW00004838       28\n",
      "6  USW00014819       38\n",
      "7  USW00094846       34\n"
     ]
    }
   ],
   "source": [
    "df_35 = pd.read_csv('Tmax35.csv', na_values = [\"NaN\"])\n",
    "df_35_clean = df_35.dropna()\n",
    "df_35_clean.reset_index()\n",
    "df_35_clean.NAME.unique()\n",
    "df_35_s = df_35_clean.sort_values([\"STATION\", \"DATE\"]).reset_index(drop=True)\n",
    "result_35 = df_35_s.groupby(\"STATION\").apply(count_hot_days).reset_index(name=\"NumDays\")\n",
    "print(result_35)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f016ecd6-3d12-4bf6-8e15-55f484760dd8",
   "metadata": {},
   "source": [
    "#### After getting the result of 8 stations of 2020-2021, 2021-2023, and 2023-2025, I add them together to get the total heatwave days of these stations in 5 years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "0560bd3f-a6d7-4f1b-8e66-01079b5149c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       STATION  NumDays\n",
      "0  USC00111550       20\n",
      "1  USC00111577       86\n",
      "2  USC00115097       32\n",
      "3  USC00116616       43\n",
      "4  USC00117457       37\n",
      "5  USW00004838       59\n",
      "6  USW00014819       86\n",
      "7  USW00094846       64\n"
     ]
    }
   ],
   "source": [
    "combined = pd.concat([result_01, result_13, result_35])\n",
    "combined = combined[~combined[\"STATION\"].str.contains(\"110\")]\n",
    "final = combined.groupby(\"STATION\", as_index=False)[\"NumDays\"].sum()\n",
    "print(final)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c97cf8c1-7040-494c-93e3-9faf2240e19f",
   "metadata": {},
   "source": [
    "#### After that, I use the original dataframe to find the latitude and longitude information for these effective stations, and merge the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "ea779a6b-d819-406d-a7d2-2b23a604a90b",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
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       "      <td>19743</td>\n",
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       "      <td>41.85580</td>\n",
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       "      <td>-87.90479</td>\n",
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       "      <td>93</td>\n",
       "      <td>43937</td>\n",
       "      <td>USW00094846</td>\n",
       "      <td>41.96017</td>\n",
       "      <td>-87.93164</td>\n",
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       "    <tr>\n",
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       "      <td>64373</td>\n",
       "      <td>USC00117457</td>\n",
       "      <td>41.60413</td>\n",
       "      <td>-88.08497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>135</td>\n",
       "      <td>65095</td>\n",
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       "      <td>41.78412</td>\n",
       "      <td>-87.75514</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>180</td>\n",
       "      <td>90538</td>\n",
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       "      <td>41.73727</td>\n",
       "      <td>-87.77734</td>\n",
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      ],
      "text/plain": [
       "   level_0  index      STATION  LATITUDE  LONGITUDE\n",
       "0        4    256  USC00115097  41.81271  -88.07275\n",
       "1       31  12778  USC00116616  41.49453  -87.67951\n",
       "2       47  19743  USC00111550  41.85580  -87.60940\n",
       "3       75  34805  USW00004838  42.12076  -87.90479\n",
       "4       93  43937  USW00094846  41.96017  -87.93164\n",
       "5      134  64373  USC00117457  41.60413  -88.08497\n",
       "6      135  65095  USW00014819  41.78412  -87.75514\n",
       "7      180  90538  USC00111577  41.73727  -87.77734"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords = df[[\"STATION\", \"LATITUDE\", \"LONGITUDE\"]].drop_duplicates().reset_index()\n",
    "final_coords = coords[coords[\"STATION\"].isin(final[\"STATION\"])].reset_index()\n",
    "final_coords"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8ac6a31-d98c-4051-94e8-cb3db7fa0650",
   "metadata": {},
   "source": [
    "#### The heatwave index is simply calculated by dividing the number of heatwave days (heatwave frequency) by 1826, the total days from 2020.10.1 to 2025.10.1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "ba48f58f-2275-4c3c-bb76-85818203f1bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.010953</td>\n",
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       "      <th>1</th>\n",
       "      <td>USC00111577</td>\n",
       "      <td>86</td>\n",
       "      <td>41.73727</td>\n",
       "      <td>-87.77734</td>\n",
       "      <td>0.047097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USC00115097</td>\n",
       "      <td>32</td>\n",
       "      <td>41.81271</td>\n",
       "      <td>-88.07275</td>\n",
       "      <td>0.017525</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USC00116616</td>\n",
       "      <td>43</td>\n",
       "      <td>41.49453</td>\n",
       "      <td>-87.67951</td>\n",
       "      <td>0.023549</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USC00117457</td>\n",
       "      <td>37</td>\n",
       "      <td>41.60413</td>\n",
       "      <td>-88.08497</td>\n",
       "      <td>0.020263</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
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       "      <td>59</td>\n",
       "      <td>42.12076</td>\n",
       "      <td>-87.90479</td>\n",
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       "    <tr>\n",
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       "      <td>USW00014819</td>\n",
       "      <td>86</td>\n",
       "      <td>41.78412</td>\n",
       "      <td>-87.75514</td>\n",
       "      <td>0.047097</td>\n",
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       "    <tr>\n",
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       "      <td>USW00094846</td>\n",
       "      <td>64</td>\n",
       "      <td>41.96017</td>\n",
       "      <td>-87.93164</td>\n",
       "      <td>0.035049</td>\n",
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      ],
      "text/plain": [
       "       STATION  NumDays  LATITUDE  LONGITUDE  heatwave_index\n",
       "0  USC00111550       20  41.85580  -87.60940        0.010953\n",
       "1  USC00111577       86  41.73727  -87.77734        0.047097\n",
       "2  USC00115097       32  41.81271  -88.07275        0.017525\n",
       "3  USC00116616       43  41.49453  -87.67951        0.023549\n",
       "4  USC00117457       37  41.60413  -88.08497        0.020263\n",
       "5  USW00004838       59  42.12076  -87.90479        0.032311\n",
       "6  USW00014819       86  41.78412  -87.75514        0.047097\n",
       "7  USW00094846       64  41.96017  -87.93164        0.035049"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_with_coords = final.merge(final_coords[[\"STATION\", \"LATITUDE\", \"LONGITUDE\"]], on=\"STATION\", how=\"left\")\n",
    "final_with_coords[\"heatwave_index\"] = final_with_coords[\"NumDays\"] / 1826\n",
    "final_with_coords"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c7366a1-39bb-4af9-8dd4-442fa06ed3d4",
   "metadata": {},
   "source": [
    "#### At last, I connect the result with folium, and present the data on folium. I record the location of the stations on the map as seperate points, and when clicking the point, we can get the heatwave frequency and heatwave index for these stations for 2020-2025."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e7139388-5b7b-4bbd-9814-99d051a9f55c",
   "metadata": {},
   "outputs": [
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       "            &lt;style&gt;\n",
       "                #map_a1bb60021d40f07ea074c16b64945d26 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "                .leaflet-container { font-size: 1rem; }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;\n",
       "    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_a1bb60021d40f07ea074c16b64945d26&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;\n",
       "    \n",
       "    \n",
       "            var map_a1bb60021d40f07ea074c16b64945d26 = L.map(\n",
       "                &quot;map_a1bb60021d40f07ea074c16b64945d26&quot;,\n",
       "                {\n",
       "                    center: [41.8781, -87.6298],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 10,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_80f5af49a998273216b4efacd433f13c = L.tileLayer(\n",
       "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "            var marker_ec33df1608233d50338aa5c5eb564350 = L.marker(\n",
       "                [41.8781, -87.6298],\n",
       "                {}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "            var icon_5e49e7365c7c1ceaa5b6f98b2b7862cb = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;info-sign&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;red&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_ec33df1608233d50338aa5c5eb564350.setIcon(icon_5e49e7365c7c1ceaa5b6f98b2b7862cb);\n",
       "        \n",
       "    \n",
       "        var popup_88f21ca4cdd4b4da6ea3c0d71e686dad = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_45c7b5b0e167fe6ee113153383e6989b = $(`&lt;div id=&quot;html_45c7b5b0e167fe6ee113153383e6989b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Chicago Downtown&lt;/div&gt;`)[0];\n",
       "                popup_88f21ca4cdd4b4da6ea3c0d71e686dad.setContent(html_45c7b5b0e167fe6ee113153383e6989b);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_ec33df1608233d50338aa5c5eb564350.bindPopup(popup_88f21ca4cdd4b4da6ea3c0d71e686dad)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            marker_ec33df1608233d50338aa5c5eb564350.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     Click for more info\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_9c4e25fb47d272ca6ea4429f5f6f01ea = L.circleMarker(\n",
       "                [41.8558, -87.6094],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_e28c2dde8ce429edcac414e0a7eb0fe5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_d0fea1f4f5560f25ada69b51a6ba6842 = $(`&lt;div id=&quot;html_d0fea1f4f5560f25ada69b51a6ba6842&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USC00111550&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0110&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 20&lt;/div&gt;`)[0];\n",
       "                popup_e28c2dde8ce429edcac414e0a7eb0fe5.setContent(html_d0fea1f4f5560f25ada69b51a6ba6842);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_9c4e25fb47d272ca6ea4429f5f6f01ea.bindPopup(popup_e28c2dde8ce429edcac414e0a7eb0fe5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_9c4e25fb47d272ca6ea4429f5f6f01ea.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USC00111550\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_f6cf456120fd6bc2109b3a9167f62557 = L.circleMarker(\n",
       "                [41.73727, -87.77734],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_6945da921645f8d3d4fcffb53158b508 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_0e2ebd4956c94ebede1dd02d86f472b5 = $(`&lt;div id=&quot;html_0e2ebd4956c94ebede1dd02d86f472b5&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USC00111577&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0471&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 86&lt;/div&gt;`)[0];\n",
       "                popup_6945da921645f8d3d4fcffb53158b508.setContent(html_0e2ebd4956c94ebede1dd02d86f472b5);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_f6cf456120fd6bc2109b3a9167f62557.bindPopup(popup_6945da921645f8d3d4fcffb53158b508)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_f6cf456120fd6bc2109b3a9167f62557.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USC00111577\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_af9781248ddbdd1aac4e04317affd2c7 = L.circleMarker(\n",
       "                [41.81271, -88.07275],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_f4715cc9407462c55d4a70c96d31a122 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_aacbd42210296ea6594142f8d885ff45 = $(`&lt;div id=&quot;html_aacbd42210296ea6594142f8d885ff45&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USC00115097&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0175&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 32&lt;/div&gt;`)[0];\n",
       "                popup_f4715cc9407462c55d4a70c96d31a122.setContent(html_aacbd42210296ea6594142f8d885ff45);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_af9781248ddbdd1aac4e04317affd2c7.bindPopup(popup_f4715cc9407462c55d4a70c96d31a122)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_af9781248ddbdd1aac4e04317affd2c7.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USC00115097\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_0882acd50516c8655945da047b349eda = L.circleMarker(\n",
       "                [41.49453, -87.67951],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_5cf683ea725e9f5cf122cb35f7a22dc8 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_f11b5de99f5548495af8bf95e5e1a16b = $(`&lt;div id=&quot;html_f11b5de99f5548495af8bf95e5e1a16b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USC00116616&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0235&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 43&lt;/div&gt;`)[0];\n",
       "                popup_5cf683ea725e9f5cf122cb35f7a22dc8.setContent(html_f11b5de99f5548495af8bf95e5e1a16b);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_0882acd50516c8655945da047b349eda.bindPopup(popup_5cf683ea725e9f5cf122cb35f7a22dc8)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_0882acd50516c8655945da047b349eda.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USC00116616\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_37fd3e82cb099a428ee2a762d6245935 = L.circleMarker(\n",
       "                [41.60413, -88.08497],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_17e575160a12d40c17f120c922ed8ba0 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_5716b2489464c8701c3a4d801e2241ad = $(`&lt;div id=&quot;html_5716b2489464c8701c3a4d801e2241ad&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USC00117457&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0203&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 37&lt;/div&gt;`)[0];\n",
       "                popup_17e575160a12d40c17f120c922ed8ba0.setContent(html_5716b2489464c8701c3a4d801e2241ad);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_37fd3e82cb099a428ee2a762d6245935.bindPopup(popup_17e575160a12d40c17f120c922ed8ba0)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_37fd3e82cb099a428ee2a762d6245935.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USC00117457\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_40084a5f17ee8b965906d72bd5aaef1f = L.circleMarker(\n",
       "                [42.12076, -87.90479],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_df1a992bb9489115c3fd767aaefaafd0 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_6709abc32e4d7729b5cd5acbce3a1e93 = $(`&lt;div id=&quot;html_6709abc32e4d7729b5cd5acbce3a1e93&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USW00004838&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0323&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 59&lt;/div&gt;`)[0];\n",
       "                popup_df1a992bb9489115c3fd767aaefaafd0.setContent(html_6709abc32e4d7729b5cd5acbce3a1e93);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_40084a5f17ee8b965906d72bd5aaef1f.bindPopup(popup_df1a992bb9489115c3fd767aaefaafd0)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_40084a5f17ee8b965906d72bd5aaef1f.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USW00004838\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_673f99481ac7ecfcfff9e8f29fc21744 = L.circleMarker(\n",
       "                [41.78412, -87.75514],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_0bea82ec5ce521df9ef769525a119bb4 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_ac1645228a525c3bb739c94d9821ab2e = $(`&lt;div id=&quot;html_ac1645228a525c3bb739c94d9821ab2e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USW00014819&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0471&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 86&lt;/div&gt;`)[0];\n",
       "                popup_0bea82ec5ce521df9ef769525a119bb4.setContent(html_ac1645228a525c3bb739c94d9821ab2e);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_673f99481ac7ecfcfff9e8f29fc21744.bindPopup(popup_0bea82ec5ce521df9ef769525a119bb4)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_673f99481ac7ecfcfff9e8f29fc21744.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USW00014819\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var circle_marker_b84649ef9997f2c608cd29ef4fcdbcfe = L.circleMarker(\n",
       "                [41.96017, -87.93164],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;blue&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;orange&quot;, &quot;fillOpacity&quot;: 0.7, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 8, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_a1bb60021d40f07ea074c16b64945d26);\n",
       "        \n",
       "    \n",
       "        var popup_4df60ffbc5b5ef6cbd2c77ad00b5bd1d = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_edf39ca0de1875efa6f10305c0b09538 = $(`&lt;div id=&quot;html_edf39ca0de1875efa6f10305c0b09538&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;&lt;b&gt;Station:&lt;/b&gt; USW00094846&lt;br&gt;&lt;b&gt;Heatwave Index:&lt;/b&gt; 0.0350&lt;br&gt;&lt;b&gt;NumDays:&lt;/b&gt; 64&lt;/div&gt;`)[0];\n",
       "                popup_4df60ffbc5b5ef6cbd2c77ad00b5bd1d.setContent(html_edf39ca0de1875efa6f10305c0b09538);\n",
       "            \n",
       "        \n",
       "\n",
       "        circle_marker_b84649ef9997f2c608cd29ef4fcdbcfe.bindPopup(popup_4df60ffbc5b5ef6cbd2c77ad00b5bd1d)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            circle_marker_b84649ef9997f2c608cd29ef4fcdbcfe.bindTooltip(\n",
       "                `&lt;div&gt;\n",
       "                     USW00094846\n",
       "                 &lt;/div&gt;`,\n",
       "                {&quot;sticky&quot;: true}\n",
       "            );\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 0x7fe2c5d967c0>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import folium\n",
    "\n",
    "def plot_chicago(final_with_coords):\n",
    "    chicago_center = [41.8781, -87.6298]\n",
    "    m = folium.Map(location=chicago_center, zoom_start=10, tiles='OpenStreetMap')\n",
    "    folium.Marker(\n",
    "        chicago_center,\n",
    "        popup='Chicago Downtown',\n",
    "        tooltip='Click for more info',\n",
    "        icon=folium.Icon(color='red', icon='info-sign')\n",
    "    ).add_to(m)\n",
    "    for _, row in final_with_coords.iterrows():\n",
    "        folium.CircleMarker(\n",
    "            location=[row[\"LATITUDE\"], row[\"LONGITUDE\"]],\n",
    "            radius=8,\n",
    "            color='blue',\n",
    "            fill=True,\n",
    "            fill_color='orange',\n",
    "            fill_opacity=0.7,\n",
    "            popup=(\n",
    "                f\"<b>Station:</b> {row['STATION']}<br>\"\n",
    "                f\"<b>Heatwave Index:</b> {row['heatwave_index']:.4f}<br>\"\n",
    "                f\"<b>NumDays:</b> {row['NumDays']}\"\n",
    "            ),\n",
    "            tooltip=f\"{row['STATION']}\"\n",
    "        ).add_to(m)\n",
    "    return m\n",
    "m = plot_chicago(final_with_coords)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a93600e-2e0d-403b-9e9b-fe70cef33632",
   "metadata": {},
   "source": [
    "#### We can see that the stations that are closer to Chicago downtown has higher heatwave frequency, while the stations in suburban areas has lower heatwave frequency. The station with index USC00111550 is an exception, maybe because it is very close to the Michigan Lake. "
   ]
  }
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