VacationPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4cc0ea1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the dependencies.\n",
    "import pandas as pd\n",
    "import gmaps\n",
    "import requests\n",
    "# Import the API key.\n",
    "from config import g_key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "59c2d449",
   "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>City_ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>East London</td>\n",
       "      <td>-33.0153</td>\n",
       "      <td>27.9116</td>\n",
       "      <td>68.14</td>\n",
       "      <td>72</td>\n",
       "      <td>84</td>\n",
       "      <td>10.25</td>\n",
       "      <td>ZA</td>\n",
       "      <td>2021-12-07 16:12:54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Ternate</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>127.4000</td>\n",
       "      <td>81.54</td>\n",
       "      <td>84</td>\n",
       "      <td>100</td>\n",
       "      <td>11.25</td>\n",
       "      <td>ID</td>\n",
       "      <td>2021-12-07 16:12:54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Shubarshi</td>\n",
       "      <td>48.5872</td>\n",
       "      <td>57.1869</td>\n",
       "      <td>27.39</td>\n",
       "      <td>89</td>\n",
       "      <td>54</td>\n",
       "      <td>8.84</td>\n",
       "      <td>KZ</td>\n",
       "      <td>2021-12-07 16:12:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Albany</td>\n",
       "      <td>42.6001</td>\n",
       "      <td>-73.9662</td>\n",
       "      <td>37.45</td>\n",
       "      <td>70</td>\n",
       "      <td>40</td>\n",
       "      <td>1.99</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-12-07 16:08:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Egvekinot</td>\n",
       "      <td>66.3167</td>\n",
       "      <td>-179.1667</td>\n",
       "      <td>-5.08</td>\n",
       "      <td>99</td>\n",
       "      <td>100</td>\n",
       "      <td>2.13</td>\n",
       "      <td>RU</td>\n",
       "      <td>2021-12-07 16:12:55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City_ID         City      Lat       Lng  Max Temp  Humidity  Cloudiness  \\\n",
       "0        0  East London -33.0153   27.9116     68.14        72          84   \n",
       "1        1      Ternate   0.8000  127.4000     81.54        84         100   \n",
       "2        2    Shubarshi  48.5872   57.1869     27.39        89          54   \n",
       "3        3       Albany  42.6001  -73.9662     37.45        70          40   \n",
       "4        4    Egvekinot  66.3167 -179.1667     -5.08        99         100   \n",
       "\n",
       "   Wind Speed Country                 Date  \n",
       "0       10.25      ZA  2021-12-07 16:12:54  \n",
       "1       11.25      ID  2021-12-07 16:12:54  \n",
       "2        8.84      KZ  2021-12-07 16:12:55  \n",
       "3        1.99      US  2021-12-07 16:08:50  \n",
       "4        2.13      RU  2021-12-07 16:12:55  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Store the CSV you saved created in part one into a DataFrame.\n",
    "city_data_df = pd.read_csv(\"weather_data/cities.csv\")\n",
    "city_data_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1b8f396e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID         int64\n",
       "City           object\n",
       "Lat           float64\n",
       "Lng           float64\n",
       "Max Temp      float64\n",
       "Humidity        int64\n",
       "Cloudiness      int64\n",
       "Wind Speed    float64\n",
       "Country        object\n",
       "Date           object\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c933606c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure gmaps to use your Google API key.\n",
    "gmaps.configure(api_key=g_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ee679a78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bd54c8233cf84fdb8e7aa4e31f60869e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. Assign the locations to an array of latitude and longitude pairs.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "\n",
    "# 2. Assign the weights variable to some values.\n",
    "temperatures = city_data_df[\"Humidity\"]\n",
    "max_temp = temperatures.max()\n",
    "\n",
    "# 3. Assign the figure variable to the gmaps.figure() attribute.\n",
    "fig = gmaps.figure()\n",
    "\n",
    "# 4. Assign the heatmap_layer variable to the heatmap_layer attribute and add in the locations.\n",
    "heatmap_layer = gmaps.heatmap_layer(locations, weights=temperatures)\n",
    "\n",
    "# 5. Add the heatmap layer.\n",
    "fig.add_layer(heatmap_layer)\n",
    "# 6. Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4cb75cdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the maximum temperature.\n",
    "max_temp = city_data_df[\"Max Temp\"]\n",
    "temps = []\n",
    "for temp in max_temp:\n",
    "    temps.append(max(temp, 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "15354a04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ebd4754b0a57435ea8f5858860e9466b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. Assign the locations to an array of latitude and longitude pairs.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "\n",
    "# 2. Assign the weights variable to some values.\n",
    "temperatures = city_data_df[\"Humidity\"]\n",
    "max_temp = temperatures.max()\n",
    "\n",
    "# 3. Assign the figure variable to the gmaps.figure() attribute.\n",
    "fig = gmaps.figure()\n",
    "\n",
    "# 4. Assign the heatmap_layer variable to the heatmap_layer attribute and add in the locations.\n",
    "heatmap_layer = gmaps.heatmap_layer(locations, weights=temperatures)\n",
    "\n",
    "# 5. Add the heatmap layer.\n",
    "fig.add_layer(heatmap_layer)\n",
    "# 6. Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "be895d40",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the maximum temperature.\n",
    "max_temp = city_data_df[\"Max Temp\"]\n",
    "temps = []\n",
    "for temp in max_temp:\n",
    "    temps.append(max(temp, 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ee103723",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eb8dc2533e164c698337226b89433011",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. Assign the locations to an array of latitude and longitude pairs.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "\n",
    "# 2. Assign the weights variable to some values.\n",
    "temperatures = city_data_df[\"Humidity\"]\n",
    "max_temp = temperatures.max()\n",
    "\n",
    "# 3. Assign the figure variable to the gmaps.figure() attribute.\n",
    "fig = gmaps.figure()\n",
    "\n",
    "# 4. Assign the heatmap_layer variable to the heatmap_layer attribute and add in the locations.\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=[max(temp, 0) for temp in temperatures])\n",
    "\n",
    "# 5. Add the heatmap layer.\n",
    "fig.add_layer(heatmap_layer)\n",
    "# 6. Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9b76eb5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Adjust Heatmap Zoom, Intensity, and Point Radius"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7cfcba28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6b3e3f1cae2447d9a867dc41493e8a67",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. Assign the locations to an array of latitude and longitude pairs.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "\n",
    "# 2. Assign the weights variable to some values.\n",
    "temperatures = city_data_df[\"Humidity\"]\n",
    "max_temp = temperatures.max()\n",
    "\n",
    "# 3. Assign the figure variable to the gmaps.figure() attribute.\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "\n",
    "# 4. Assign the heatmap_layer variable to the heatmap_layer attribute and add in the locations.\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=[max(temp, 0) for temp in temperatures])\n",
    "\n",
    "# 5. Add the heatmap layer.\n",
    "fig.add_layer(heatmap_layer)\n",
    "# 6. Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9708c86d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "976f0f62017e4a1aa07d7d0c7962eec7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. Assign the locations to an array of latitude and longitude pairs.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "\n",
    "# 2. Assign the weights variable to some values.\n",
    "temperatures = city_data_df[\"Humidity\"]\n",
    "max_temp = temperatures.max()\n",
    "\n",
    "# 3. Assign the figure variable to the gmaps.figure() attribute.\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "\n",
    "# 4. Assign the heatmap_layer variable to the heatmap_layer attribute and add in the locations.\n",
    "# heat_layer = gmaps.heatmap_layer(locations, weights=[max(temp, 0) for temp in temperatures])\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=temps, dissipating=False, max_intensity=300, point_radius=4)\n",
    "\n",
    "# 5. Add the heatmap layer.\n",
    "fig.add_layer(heatmap_layer)\n",
    "\n",
    "# 6. Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4b44c1b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b27e9a9a6b804ad4afd5c8a9e7eaa7ab",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap of percent humidity\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "humidity = city_data_df[\"Humidity\"]\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=humidity, dissipating=False, max_intensity=300, point_radius=4)\n",
    "\n",
    "fig.add_layer(heat_layer)\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f387e446",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8d6a420b97594083b36c41b1ca3303ab",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a Percent Cloudiness Heatmap\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "clouds = city_data_df[\"Cloudiness\"] \n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=clouds, dissipating=False, max_intensity=300, point_radius=4)\n",
    "\n",
    "fig.add_layer(heat_layer)\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9d4c1623",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "80d83fa424f54162bcdfa220e8e37289",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a Wind Speed Heatmap\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "wind = city_data_df[\"Wind Speed\"]\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=wind, dissipating=False, max_intensity=300, point_radius=4)\n",
    "\n",
    "fig.add_layer(heat_layer)\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d67a14fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Maximum Temperature Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2e10e90b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     City_ID         City      Lat       Lng  Max Temp  Humidity  Cloudiness  \\\n",
      "0          0  East London -33.0153   27.9116     68.14        72          84   \n",
      "1          1      Ternate   0.8000  127.4000     81.54        84         100   \n",
      "2          2    Shubarshi  48.5872   57.1869     27.39        89          54   \n",
      "3          3       Albany  42.6001  -73.9662     37.45        70          40   \n",
      "4          4    Egvekinot  66.3167 -179.1667     -5.08        99         100   \n",
      "..       ...          ...      ...       ...       ...       ...         ...   \n",
      "554      554        Paveh  35.0434   46.3565     46.94        53          86   \n",
      "555      555      Douglas  41.3000  -96.1670     35.01        58           1   \n",
      "556      556          Sur  22.5667   59.5289     74.25        59           0   \n",
      "557      557      Sakakah  29.9697   40.2064     67.57        30          97   \n",
      "558      558      Gigmoto  13.7796  124.3900     78.04        82         100   \n",
      "\n",
      "     Wind Speed Country                 Date  \n",
      "0         10.25      ZA  2021-12-07 16:12:54  \n",
      "1         11.25      ID  2021-12-07 16:12:54  \n",
      "2          8.84      KZ  2021-12-07 16:12:55  \n",
      "3          1.99      US  2021-12-07 16:08:50  \n",
      "4          2.13      RU  2021-12-07 16:12:55  \n",
      "..          ...     ...                  ...  \n",
      "554        7.65      IR  2021-12-07 16:27:39  \n",
      "555        8.99      US  2021-12-07 16:23:13  \n",
      "556        6.11      OM  2021-12-07 16:27:39  \n",
      "557       12.62      SA  2021-12-07 16:27:40  \n",
      "558       17.76      PH  2021-12-07 16:27:40  \n",
      "\n",
      "[559 rows x 10 columns]\n"
     ]
    }
   ],
   "source": [
    "print(city_data_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2969fc81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "26efb507533642b9ad730bbd99356678",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap of temperature\n",
    "# Get the latitude and longitude.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "# Get the maximum temperature.\n",
    "max_temp = city_data_df[\"Max Temp\"]\n",
    "temps = []\n",
    "for temp in max_temp:\n",
    "    temps.append(max(temp, 0))\n",
    "# Assign the figure variable.\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "# Assign the heatmap variable.\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=[max(temp, 0) for temp in max_temp])\n",
    "# Add the heatmap layer.\n",
    "fig.add_layer(heat_layer)\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "224842a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get Vacation Criteria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "92233f23",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What is the minimum temperature you would like for your trip? 70\n",
      "What is the maximum temperature you would like for your trip? 95\n"
     ]
    }
   ],
   "source": [
    "# Ask the customer to add a minimum and maximum temperature value.\n",
    "min_temp = float(input(\"What is the minimum temperature you would like for your trip? \"))\n",
    "max_temp = float(input(\"What is the maximum temperature you would like for your trip? \"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "85d172f8",
   "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>City_ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Ternate</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>127.4000</td>\n",
       "      <td>81.54</td>\n",
       "      <td>84</td>\n",
       "      <td>100</td>\n",
       "      <td>11.25</td>\n",
       "      <td>ID</td>\n",
       "      <td>2021-12-07 16:12:54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Tra Vinh</td>\n",
       "      <td>9.9347</td>\n",
       "      <td>106.3453</td>\n",
       "      <td>72.37</td>\n",
       "      <td>92</td>\n",
       "      <td>23</td>\n",
       "      <td>0.94</td>\n",
       "      <td>VN</td>\n",
       "      <td>2021-12-07 16:12:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>Rayong</td>\n",
       "      <td>12.8333</td>\n",
       "      <td>101.4333</td>\n",
       "      <td>72.77</td>\n",
       "      <td>84</td>\n",
       "      <td>49</td>\n",
       "      <td>6.38</td>\n",
       "      <td>TH</td>\n",
       "      <td>2021-12-07 16:12:58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>Avarua</td>\n",
       "      <td>-21.2078</td>\n",
       "      <td>-159.7750</td>\n",
       "      <td>73.45</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>2.30</td>\n",
       "      <td>CK</td>\n",
       "      <td>2021-12-07 16:12:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>Atuona</td>\n",
       "      <td>-9.8000</td>\n",
       "      <td>-139.0333</td>\n",
       "      <td>78.35</td>\n",
       "      <td>74</td>\n",
       "      <td>62</td>\n",
       "      <td>20.33</td>\n",
       "      <td>PF</td>\n",
       "      <td>2021-12-07 16:13:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>Bandarbeyla</td>\n",
       "      <td>9.4942</td>\n",
       "      <td>50.8122</td>\n",
       "      <td>77.50</td>\n",
       "      <td>64</td>\n",
       "      <td>7</td>\n",
       "      <td>19.17</td>\n",
       "      <td>SO</td>\n",
       "      <td>2021-12-07 16:13:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>Saint-Pierre</td>\n",
       "      <td>-21.3393</td>\n",
       "      <td>55.4781</td>\n",
       "      <td>78.48</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>19.57</td>\n",
       "      <td>RE</td>\n",
       "      <td>2021-12-07 16:13:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>Cabo San Lucas</td>\n",
       "      <td>22.8909</td>\n",
       "      <td>-109.9124</td>\n",
       "      <td>76.51</td>\n",
       "      <td>67</td>\n",
       "      <td>75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>MX</td>\n",
       "      <td>2021-12-07 16:13:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>Kununurra</td>\n",
       "      <td>-15.7667</td>\n",
       "      <td>128.7333</td>\n",
       "      <td>80.58</td>\n",
       "      <td>83</td>\n",
       "      <td>75</td>\n",
       "      <td>5.75</td>\n",
       "      <td>AU</td>\n",
       "      <td>2021-12-07 16:13:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>35</td>\n",
       "      <td>Kahului</td>\n",
       "      <td>20.8947</td>\n",
       "      <td>-156.4700</td>\n",
       "      <td>77.85</td>\n",
       "      <td>93</td>\n",
       "      <td>40</td>\n",
       "      <td>3.44</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-12-07 16:13:05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    City_ID            City      Lat       Lng  Max Temp  Humidity  \\\n",
       "1         1         Ternate   0.8000  127.4000     81.54        84   \n",
       "7         7        Tra Vinh   9.9347  106.3453     72.37        92   \n",
       "14       14          Rayong  12.8333  101.4333     72.77        84   \n",
       "17       17          Avarua -21.2078 -159.7750     73.45       100   \n",
       "20       20          Atuona  -9.8000 -139.0333     78.35        74   \n",
       "22       22     Bandarbeyla   9.4942   50.8122     77.50        64   \n",
       "23       23    Saint-Pierre -21.3393   55.4781     78.48        75   \n",
       "25       25  Cabo San Lucas  22.8909 -109.9124     76.51        67   \n",
       "31       31       Kununurra -15.7667  128.7333     80.58        83   \n",
       "35       35         Kahului  20.8947 -156.4700     77.85        93   \n",
       "\n",
       "    Cloudiness  Wind Speed Country                 Date  \n",
       "1          100       11.25      ID  2021-12-07 16:12:54  \n",
       "7           23        0.94      VN  2021-12-07 16:12:56  \n",
       "14          49        6.38      TH  2021-12-07 16:12:58  \n",
       "17          90        2.30      CK  2021-12-07 16:12:59  \n",
       "20          62       20.33      PF  2021-12-07 16:13:00  \n",
       "22           7       19.17      SO  2021-12-07 16:13:01  \n",
       "23          75       19.57      RE  2021-12-07 16:13:01  \n",
       "25          75        0.00      MX  2021-12-07 16:13:02  \n",
       "31          75        5.75      AU  2021-12-07 16:13:04  \n",
       "35          40        3.44      US  2021-12-07 16:13:05  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter the dataset to find the cities that fit the criteria.\n",
    "preferred_cities_df = city_data_df.loc[(city_data_df[\"Max Temp\"] <= max_temp) & \\\n",
    "                                       (city_data_df[\"Max Temp\"] >= min_temp)]\n",
    "preferred_cities_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3ccc9529",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       213\n",
       "City          213\n",
       "Lat           213\n",
       "Lng           213\n",
       "Max Temp      213\n",
       "Humidity      213\n",
       "Cloudiness    213\n",
       "Wind Speed    213\n",
       "Country       210\n",
       "Date          213\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "111438e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       0\n",
       "City          0\n",
       "Lat           0\n",
       "Lng           0\n",
       "Max Temp      0\n",
       "Humidity      0\n",
       "Cloudiness    0\n",
       "Wind Speed    0\n",
       "Country       3\n",
       "Date          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c29d7597",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       213\n",
       "City          213\n",
       "Lat           213\n",
       "Lng           213\n",
       "Max Temp      213\n",
       "Humidity      213\n",
       "Cloudiness    213\n",
       "Wind Speed    213\n",
       "Country       210\n",
       "Date          213\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7a160cf0",
   "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>City_ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Wind Speed</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Ternate</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>127.4000</td>\n",
       "      <td>81.54</td>\n",
       "      <td>84</td>\n",
       "      <td>100</td>\n",
       "      <td>11.25</td>\n",
       "      <td>ID</td>\n",
       "      <td>2021-12-07 16:12:54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Tra Vinh</td>\n",
       "      <td>9.9347</td>\n",
       "      <td>106.3453</td>\n",
       "      <td>72.37</td>\n",
       "      <td>92</td>\n",
       "      <td>23</td>\n",
       "      <td>0.94</td>\n",
       "      <td>VN</td>\n",
       "      <td>2021-12-07 16:12:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>Rayong</td>\n",
       "      <td>12.8333</td>\n",
       "      <td>101.4333</td>\n",
       "      <td>72.77</td>\n",
       "      <td>84</td>\n",
       "      <td>49</td>\n",
       "      <td>6.38</td>\n",
       "      <td>TH</td>\n",
       "      <td>2021-12-07 16:12:58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>Avarua</td>\n",
       "      <td>-21.2078</td>\n",
       "      <td>-159.7750</td>\n",
       "      <td>73.45</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>2.30</td>\n",
       "      <td>CK</td>\n",
       "      <td>2021-12-07 16:12:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>Atuona</td>\n",
       "      <td>-9.8000</td>\n",
       "      <td>-139.0333</td>\n",
       "      <td>78.35</td>\n",
       "      <td>74</td>\n",
       "      <td>62</td>\n",
       "      <td>20.33</td>\n",
       "      <td>PF</td>\n",
       "      <td>2021-12-07 16:13:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>545</td>\n",
       "      <td>Grand Gaube</td>\n",
       "      <td>-20.0064</td>\n",
       "      <td>57.6608</td>\n",
       "      <td>79.20</td>\n",
       "      <td>71</td>\n",
       "      <td>4</td>\n",
       "      <td>5.01</td>\n",
       "      <td>MU</td>\n",
       "      <td>2021-12-07 16:26:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547</th>\n",
       "      <td>547</td>\n",
       "      <td>Mporokoso</td>\n",
       "      <td>-9.3727</td>\n",
       "      <td>30.1250</td>\n",
       "      <td>75.34</td>\n",
       "      <td>48</td>\n",
       "      <td>86</td>\n",
       "      <td>3.74</td>\n",
       "      <td>ZM</td>\n",
       "      <td>2021-12-07 16:27:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>552</td>\n",
       "      <td>Bitung</td>\n",
       "      <td>1.4451</td>\n",
       "      <td>125.1824</td>\n",
       "      <td>81.45</td>\n",
       "      <td>87</td>\n",
       "      <td>100</td>\n",
       "      <td>7.43</td>\n",
       "      <td>ID</td>\n",
       "      <td>2021-12-07 16:22:53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>556</td>\n",
       "      <td>Sur</td>\n",
       "      <td>22.5667</td>\n",
       "      <td>59.5289</td>\n",
       "      <td>74.25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>6.11</td>\n",
       "      <td>OM</td>\n",
       "      <td>2021-12-07 16:27:39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>558</td>\n",
       "      <td>Gigmoto</td>\n",
       "      <td>13.7796</td>\n",
       "      <td>124.3900</td>\n",
       "      <td>78.04</td>\n",
       "      <td>82</td>\n",
       "      <td>100</td>\n",
       "      <td>17.76</td>\n",
       "      <td>PH</td>\n",
       "      <td>2021-12-07 16:27:40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     City_ID         City      Lat       Lng  Max Temp  Humidity  Cloudiness  \\\n",
       "1          1      Ternate   0.8000  127.4000     81.54        84         100   \n",
       "7          7     Tra Vinh   9.9347  106.3453     72.37        92          23   \n",
       "14        14       Rayong  12.8333  101.4333     72.77        84          49   \n",
       "17        17       Avarua -21.2078 -159.7750     73.45       100          90   \n",
       "20        20       Atuona  -9.8000 -139.0333     78.35        74          62   \n",
       "..       ...          ...      ...       ...       ...       ...         ...   \n",
       "545      545  Grand Gaube -20.0064   57.6608     79.20        71           4   \n",
       "547      547    Mporokoso  -9.3727   30.1250     75.34        48          86   \n",
       "552      552       Bitung   1.4451  125.1824     81.45        87         100   \n",
       "556      556          Sur  22.5667   59.5289     74.25        59           0   \n",
       "558      558      Gigmoto  13.7796  124.3900     78.04        82         100   \n",
       "\n",
       "     Wind Speed Country                 Date  \n",
       "1         11.25      ID  2021-12-07 16:12:54  \n",
       "7          0.94      VN  2021-12-07 16:12:56  \n",
       "14         6.38      TH  2021-12-07 16:12:58  \n",
       "17         2.30      CK  2021-12-07 16:12:59  \n",
       "20        20.33      PF  2021-12-07 16:13:00  \n",
       "..          ...     ...                  ...  \n",
       "545        5.01      MU  2021-12-07 16:26:36  \n",
       "547        3.74      ZM  2021-12-07 16:27:37  \n",
       "552        7.43      ID  2021-12-07 16:22:53  \n",
       "556        6.11      OM  2021-12-07 16:27:39  \n",
       "558       17.76      PH  2021-12-07 16:27:40  \n",
       "\n",
       "[210 rows x 10 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "04a59a32",
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Hotel Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ternate</td>\n",
       "      <td>ID</td>\n",
       "      <td>81.54</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>127.4000</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Tra Vinh</td>\n",
       "      <td>VN</td>\n",
       "      <td>72.37</td>\n",
       "      <td>9.9347</td>\n",
       "      <td>106.3453</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Rayong</td>\n",
       "      <td>TH</td>\n",
       "      <td>72.77</td>\n",
       "      <td>12.8333</td>\n",
       "      <td>101.4333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Avarua</td>\n",
       "      <td>CK</td>\n",
       "      <td>73.45</td>\n",
       "      <td>-21.2078</td>\n",
       "      <td>-159.7750</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Atuona</td>\n",
       "      <td>PF</td>\n",
       "      <td>78.35</td>\n",
       "      <td>-9.8000</td>\n",
       "      <td>-139.0333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bandarbeyla</td>\n",
       "      <td>SO</td>\n",
       "      <td>77.50</td>\n",
       "      <td>9.4942</td>\n",
       "      <td>50.8122</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Saint-Pierre</td>\n",
       "      <td>RE</td>\n",
       "      <td>78.48</td>\n",
       "      <td>-21.3393</td>\n",
       "      <td>55.4781</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Cabo San Lucas</td>\n",
       "      <td>MX</td>\n",
       "      <td>76.51</td>\n",
       "      <td>22.8909</td>\n",
       "      <td>-109.9124</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Kununurra</td>\n",
       "      <td>AU</td>\n",
       "      <td>80.58</td>\n",
       "      <td>-15.7667</td>\n",
       "      <td>128.7333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Kahului</td>\n",
       "      <td>US</td>\n",
       "      <td>77.85</td>\n",
       "      <td>20.8947</td>\n",
       "      <td>-156.4700</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Country  Max Temp      Lat       Lng Hotel Name\n",
       "1          Ternate      ID     81.54   0.8000  127.4000           \n",
       "7         Tra Vinh      VN     72.37   9.9347  106.3453           \n",
       "14          Rayong      TH     72.77  12.8333  101.4333           \n",
       "17          Avarua      CK     73.45 -21.2078 -159.7750           \n",
       "20          Atuona      PF     78.35  -9.8000 -139.0333           \n",
       "22     Bandarbeyla      SO     77.50   9.4942   50.8122           \n",
       "23    Saint-Pierre      RE     78.48 -21.3393   55.4781           \n",
       "25  Cabo San Lucas      MX     76.51  22.8909 -109.9124           \n",
       "31       Kununurra      AU     80.58 -15.7667  128.7333           \n",
       "35         Kahului      US     77.85  20.8947 -156.4700           "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create DataFrame called hotel_df to store hotel names along with city, country, max temp, and coordinates.\n",
    "hotel_df = preferred_cities_df[[\"City\", \"Country\", \"Max Temp\", \"Lat\", \"Lng\"]].copy()\n",
    "hotel_df[\"Hotel Name\"] = \"\"\n",
    "hotel_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9982a225",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'html_attributions': [],\n",
       " 'next_page_token': 'Aap_uECEyPp82NqRM8voFFAsGZcDfD7dZhCQvg0QndPApw2Sdl7RPnhqo7L41-cSPAr5AH-bnVS7Vq-02n2Al2o5AuwfLAgZF1DY2ghPrkLV8gSe1zZLtC2JCCEPxmsIv3T2t8jo3FNWCKIIUFm1Od98_qO3Z5wAs65Pj7k0eYZDKZW6ZOAhEFhlgM6wKAdnzGgd9jUroH8whycngUnBhU2b_4kO2iuE2rbu3Tzyc32zP1tJYOLgklKRwz4lOLpNLI5KJoH2fLPOl2JndZ9D57dB76in-0NrfYqS6HcBKQXLVQurMrjv6PiTsIcYEKtpL4JEn9ZYozUGnZZ4TjSvTdnpA_m7SuCQKHot1f64kgQdC1nYsP0qXbHBjSc39VpY3QaRMGhel54CO2BD0x2JYP_QF1QbTETYZEnKzsjAsnxXB_HTt9F7uA2L3rQ6',\n",
       " 'results': [{'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8581126, 'lng': 2.3529277},\n",
       "    'viewport': {'northeast': {'lat': 48.8594360302915,\n",
       "      'lng': 2.354355480291502},\n",
       "     'southwest': {'lat': 48.8567380697085, 'lng': 2.351657519708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Duo',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 3840,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/107554201425443337224\">Hôtel Duo</a>'],\n",
       "     'photo_reference': 'Aap_uEBQglE_RT5f42Jvs7JFmGxym9FpZUrbSOkRqHFq5tGw9X-yGZNm-dGAudPExWKZ4xdiaoz8inFMbrRHSmspfqXwnOrpVR6k_vf2E5ms7prIDM9T6mTpQ9ZsztBkGBJYd3Q8yoVcwLaLZBHmLg41xqoUiVy9qDmPgWcMPLRHaFfVKpVm',\n",
       "     'width': 5760}],\n",
       "   'place_id': 'ChIJWU9CqB1u5kcR5P1F2SMoJmc',\n",
       "   'plus_code': {'compound_code': 'V953+65 Paris, France',\n",
       "    'global_code': '8FW4V953+65'},\n",
       "   'rating': 4.2,\n",
       "   'reference': 'ChIJWU9CqB1u5kcR5P1F2SMoJmc',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['night_club',\n",
       "    'spa',\n",
       "    'lodging',\n",
       "    'bar',\n",
       "    'gym',\n",
       "    'health',\n",
       "    'point_of_interest',\n",
       "    'establishment'],\n",
       "   'user_ratings_total': 310,\n",
       "   'vicinity': '11 Rue du Temple, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8582861, 'lng': 2.3464944},\n",
       "    'viewport': {'northeast': {'lat': 48.85954748029151,\n",
       "      'lng': 2.347782830291502},\n",
       "     'southwest': {'lat': 48.85684951970851, 'lng': 2.345084869708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Britannique - Paris Centre',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 1426,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/108984000175492464929\">Hôtel Britannique - Paris Centre</a>'],\n",
       "     'photo_reference': 'Aap_uECCG8wFlxpRyBAJcWbOGI2mngIHWEgarOKS-bombunvWxD1cQIsa0d6Ed-Bq3IhLIX3RD424WNWT8dHEiUOW1b7PRLEIcCsZfr4tn6Oj9ttFBA6ry1QBCnp8oRPz-zc4CbcNHCgVhjNe6BVPTZYhraBw5bi1RRSRypVTFEuh9E687u9',\n",
       "     'width': 1476}],\n",
       "   'place_id': 'ChIJ-4Siox9u5kcRm9vM6DcMXyU',\n",
       "   'plus_code': {'compound_code': 'V85W+8H Paris, France',\n",
       "    'global_code': '8FW4V85W+8H'},\n",
       "   'rating': 4.6,\n",
       "   'reference': 'ChIJ-4Siox9u5kcRm9vM6DcMXyU',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 648,\n",
       "   'vicinity': '20 Avenue Victoria, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8606655, 'lng': 2.3469293},\n",
       "    'viewport': {'northeast': {'lat': 48.8617653302915,\n",
       "      'lng': 2.348020880291502},\n",
       "     'southwest': {'lat': 48.85906736970851, 'lng': 2.345322919708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Citadines Les Halles Paris',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 853,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/102565262508115704337\">Citadines Les Halles Paris (Apart hotel Paris)</a>'],\n",
       "     'photo_reference': 'Aap_uEBmaS4Chs6m7QxWBLzeAHMq0a-ArS4DMpm8TfJyOWzVysZG83S-p9fffRKa0gYA2Xz2Gg211BNUc8-4GjCPxtHmVldyx25aN_zA98He4np77yu7C9anXTYsdMxq2k6sPBAhqK3EdDuY7wnzSVYsrQw21iZjHkVjQ8--nWKzOPeFfKp9',\n",
       "     'width': 1280}],\n",
       "   'place_id': 'ChIJQ_QDrxhu5kcRJzNxLLEOSfU',\n",
       "   'plus_code': {'compound_code': 'V86W+7Q Paris, France',\n",
       "    'global_code': '8FW4V86W+7Q'},\n",
       "   'rating': 4.1,\n",
       "   'reference': 'ChIJQ_QDrxhu5kcRJzNxLLEOSfU',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 872,\n",
       "   'vicinity': '4 Rue des Innocents, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8607658, 'lng': 2.3465318},\n",
       "    'viewport': {'northeast': {'lat': 48.8620584302915,\n",
       "      'lng': 2.347692880291501},\n",
       "     'southwest': {'lat': 48.85936046970851, 'lng': 2.344994919708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Novotel Paris Les Halles',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 2000,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/111815616573299411056\">Novotel Paris Les Halles</a>'],\n",
       "     'photo_reference': 'Aap_uECyc3MsOI9zyY9qXbeb4Y7pfruaFV6Awu1IwA2PAYj3olHgEuIvIHp7hntgRDQf0CGS4b1X55Qu3nFe3oY5_jwfYQXpNXnpSlOk8k7xHMziP3KLih5CHWkwb0tOxAw5oLEUO28GrOFR4abhjRFMbf0Ob1X4W7NsdSFHn-usz-Ejk_Xu',\n",
       "     'width': 3000}],\n",
       "   'place_id': 'ChIJGW2pNx9u5kcRI3oyL8NG5BQ',\n",
       "   'plus_code': {'compound_code': 'V86W+8J Paris, France',\n",
       "    'global_code': '8FW4V86W+8J'},\n",
       "   'rating': 4.4,\n",
       "   'reference': 'ChIJGW2pNx9u5kcRI3oyL8NG5BQ',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 2302,\n",
       "   'vicinity': '8 Place Marguerite de Navarre, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.860352, 'lng': 2.3440948},\n",
       "    'viewport': {'northeast': {'lat': 48.86165553029149,\n",
       "      'lng': 2.345549080291502},\n",
       "     'southwest': {'lat': 48.8589575697085, 'lng': 2.342851119708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Ducs de Bourgogne',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 1390,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/101411638353598558320\">Hôtel Ducs de Bourgogne</a>'],\n",
       "     'photo_reference': 'Aap_uECCXAikmbbdFOnF7gcuzr3gMDfRsd6zFJZlqmjfl4m0k4fsVCDZGEOxiyvvk-mTiZcBZvMMIu5fiLdH98DdgC0ACZ2txZYscu-jYb-UugO-4gJY8Gsrg2ghp8KSR6PhqLnsz1zV2cKSK5Avcwr-aQUbZQ1ENT2H0yDExn_50GP7e8hU',\n",
       "     'width': 2048}],\n",
       "   'place_id': 'ChIJifTG5yFu5kcRdnisbwxnAx4',\n",
       "   'plus_code': {'compound_code': 'V86V+4J Paris, France',\n",
       "    'global_code': '8FW4V86V+4J'},\n",
       "   'rating': 4.5,\n",
       "   'reference': 'ChIJifTG5yFu5kcRdnisbwxnAx4',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 280,\n",
       "   'vicinity': '19 Rue du Pont Neuf, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8555091, 'lng': 2.3408736},\n",
       "    'viewport': {'northeast': {'lat': 48.8569076302915,\n",
       "      'lng': 2.342319280291502},\n",
       "     'southwest': {'lat': 48.8542096697085, 'lng': 2.339621319708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Citadines Saint-Germain-des-Prés Paris (Apart hotel Paris)',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 4480,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/113188832595116816387\">Citadines Saint-Germain-des-Prés Paris</a>'],\n",
       "     'photo_reference': 'Aap_uECQJ81skKLqe4CD1fpKF5jdlup-t6nz039Q5x37ZLK4S-PcHrTa83iOTy9Y9K5CKpxj04umKI_KOwRjyT4Mlnwt17p_NDOadAquKoaqXBy6d5k8I8RgteULAgbQoxhwP9ejKJLqjqaAQOveqGqc4VKTEfm7YgourqTgVD4oissAMVuY',\n",
       "     'width': 6720}],\n",
       "   'place_id': 'ChIJo5pYcN9x5kcRERXdocMgqmE',\n",
       "   'plus_code': {'compound_code': 'V84R+68 Paris, France',\n",
       "    'global_code': '8FW4V84R+68'},\n",
       "   'rating': 4.3,\n",
       "   'reference': 'ChIJo5pYcN9x5kcRERXdocMgqmE',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 717,\n",
       "   'vicinity': '53 ter Quai des Grands Augustins, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8663519, 'lng': 2.3606461},\n",
       "    'viewport': {'northeast': {'lat': 48.86775308029149,\n",
       "      'lng': 2.361905130291502},\n",
       "     'southwest': {'lat': 48.8650551197085, 'lng': 2.359207169708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Paris France Hôtel',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 2673,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/102332962500946068613\">Paris France Hôtel</a>'],\n",
       "     'photo_reference': 'Aap_uECkPEmo-viqUj80K6zvTYIbVcPoMzeOuX0c6E9GS6vrlr55Vfk95ohKSBQL5m9Ffdki762AmLf70Le99jdwbDZglmjSCgQ8UCz3qw5v5zgsRTFoYEmYjpOokuolmlOb9As36Ux-22SQz7fsWynXwE9doBgAg0NJm_PXp2NZKn6mtwwH',\n",
       "     'width': 3463}],\n",
       "   'place_id': 'ChIJhXWLZg9u5kcRDVyqoZYgcmg',\n",
       "   'plus_code': {'compound_code': 'V986+G7 Paris, France',\n",
       "    'global_code': '8FW4V986+G7'},\n",
       "   'rating': 4.3,\n",
       "   'reference': 'ChIJhXWLZg9u5kcRDVyqoZYgcmg',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 396,\n",
       "   'vicinity': '72 Rue de Turbigo, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.86386539999999, 'lng': 2.3325488},\n",
       "    'viewport': {'northeast': {'lat': 48.8650759802915,\n",
       "      'lng': 2.333775730291502},\n",
       "     'southwest': {'lat': 48.8623780197085, 'lng': 2.331077769708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hotel Regina Louvre',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 3700,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/109908333790946649027\">Hôtel Regina Louvre</a>'],\n",
       "     'photo_reference': 'Aap_uECMNS0ROUzpHYC4r0tEemLy6JX3OF9Cg6NC3ud_gCaLXex9XRJhE5dfjnAZz9yy-UIcEodAa_CeWdX21Bi-PS7GYs_wkLiwfnY5xH_OGhty8oHLGsqgAU5lX0bZyQ5d6V9jSvRWbM63eL5BnMIa3EqgehSYhp4mA4PmjW5irvCi2oJe',\n",
       "     'width': 5550}],\n",
       "   'place_id': 'ChIJP_-HCS9u5kcRsj9b1x7Pl8w',\n",
       "   'plus_code': {'compound_code': 'V87M+G2 Paris, France',\n",
       "    'global_code': '8FW4V87M+G2'},\n",
       "   'rating': 4.4,\n",
       "   'reference': 'ChIJP_-HCS9u5kcRsj9b1x7Pl8w',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging',\n",
       "    'bar',\n",
       "    'restaurant',\n",
       "    'food',\n",
       "    'point_of_interest',\n",
       "    'establishment'],\n",
       "   'user_ratings_total': 508,\n",
       "   'vicinity': '2 Place des Pyramides, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.84795229999999, 'lng': 2.370869},\n",
       "    'viewport': {'northeast': {'lat': 48.8492035302915,\n",
       "      'lng': 2.372290080291501},\n",
       "     'southwest': {'lat': 48.8465055697085, 'lng': 2.369592119708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'ibis Paris Gare de Lyon Ledru Rollin 12ème',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 2048,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/101181280085797863615\">Kevin Nguyen</a>'],\n",
       "     'photo_reference': 'Aap_uEB0EXYgicmZEtYLegm9hpqDboXEfS4EcLZY1Xx_jtOiS1BUO8dZ_v-oLh3z3v0Dsu5qBPFmgTmU9NaZjhz7vpFcTNXvSMcnE4AFfgb8Xif_MuEN4IYZae_Ty0XEY28UqCXKV6UfC7B5i5kPX9LaVazcx9G5st0nUk4Plc5wt4ULFMee',\n",
       "     'width': 1536}],\n",
       "   'place_id': 'ChIJ9RNxcQNy5kcRnZJ4vsuXcow',\n",
       "   'plus_code': {'compound_code': 'R9XC+58 Paris, France',\n",
       "    'global_code': '8FW4R9XC+58'},\n",
       "   'rating': 4.1,\n",
       "   'reference': 'ChIJ9RNxcQNy5kcRnZJ4vsuXcow',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 843,\n",
       "   'vicinity': '41/43 Avenue Ledru Rollin, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8710647, 'lng': 2.34991},\n",
       "    'viewport': {'northeast': {'lat': 48.87241888029151,\n",
       "      'lng': 2.351188530291502},\n",
       "     'southwest': {'lat': 48.86972091970851, 'lng': 2.348490569708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel des Comédies Paris',\n",
       "   'photos': [{'height': 4000,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/114696623290303183213\">Noble</a>'],\n",
       "     'photo_reference': 'Aap_uEC5bgtYQOYCHjYMDtSxklaU_0h19gjZeAFrEeOEkU-uuTCgzJq9VTr61k1e6zINX1FkAh2udShLt1KWzeTl8CJcweZ5IIeE382KFZHidsQkCpbgrnUpY6LotHEodk9MyuILblJivQml63aZ6McAG-U2ZhdV_D6Uo48ID5SrZlO7Gh-r',\n",
       "     'width': 3000}],\n",
       "   'place_id': 'ChIJn6ginxZu5kcRmAEK0OHm0cI',\n",
       "   'plus_code': {'compound_code': 'V8CX+CX Paris, France',\n",
       "    'global_code': '8FW4V8CX+CX'},\n",
       "   'rating': 4.2,\n",
       "   'reference': 'ChIJn6ginxZu5kcRmAEK0OHm0cI',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 199,\n",
       "   'vicinity': \"8 Rue d'Hauteville, Paris\"},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.84754640000001, 'lng': 2.3718722},\n",
       "    'viewport': {'northeast': {'lat': 48.8488820802915,\n",
       "      'lng': 2.373123430291502},\n",
       "     'southwest': {'lat': 48.8461841197085, 'lng': 2.370425469708499}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel De France Gare de Lyon Bastille',\n",
       "   'photos': [{'height': 787,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/117462031751048846575\">Hôtel De France Gare de Lyon Bastille</a>'],\n",
       "     'photo_reference': 'Aap_uECPJj4v9ttgXxUSS_AuO4TOsvwqxbyvj8wCq89WN6CzkfOWlFqmT_ZE1S4h3HR6dYxeqZHVKZTvAM4RvCEFdnd-0jskFh4dbl3g1CC7dL9af6_YYi3GZ8f8vCRtg_8tWQa1O0-mW5Ng9YCnPl40_JRnj56fq6Z7Cy4I1Tuc3yLjlMEw',\n",
       "     'width': 1181}],\n",
       "   'place_id': 'ChIJz6DBYgNy5kcRhOu1LhDIECM',\n",
       "   'plus_code': {'compound_code': 'R9XC+2P Paris, France',\n",
       "    'global_code': '8FW4R9XC+2P'},\n",
       "   'rating': 3.3,\n",
       "   'reference': 'ChIJz6DBYgNy5kcRhOu1LhDIECM',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 382,\n",
       "   'vicinity': '12 Rue de Lyon, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8717386, 'lng': 2.3447052},\n",
       "    'viewport': {'northeast': {'lat': 48.8731374802915,\n",
       "      'lng': 2.346059980291502},\n",
       "     'southwest': {'lat': 48.8704395197085, 'lng': 2.343362019708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Prélude Opéra Paris',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 2448,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/106224131803115407650\">Marcin Marczak</a>'],\n",
       "     'photo_reference': 'Aap_uEDlC6cN19U9U3buTbKC1K3_hG7H-mdv2GbkyN2aj8kzfETGS-vjL9CO0o9nnGZTuSglccTdFX1ij2B3xhgkymmiKsf0mobKGQKazETBxhJ0HLFQ4hPuo5EUlp3UFbdFzJy7TYhBdn7Li5KOJ9UipNf1qxY_O3LbtNb5HrC9FEp4iYUf',\n",
       "     'width': 3264}],\n",
       "   'place_id': 'ChIJ8e3Qcj5u5kcR2MIGwNxustk',\n",
       "   'plus_code': {'compound_code': 'V8CV+MV Paris, France',\n",
       "    'global_code': '8FW4V8CV+MV'},\n",
       "   'rating': 4.2,\n",
       "   'reference': 'ChIJ8e3Qcj5u5kcR2MIGwNxustk',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 391,\n",
       "   'vicinity': '8 Cité Bergère, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8423434, 'lng': 2.3632087},\n",
       "    'viewport': {'northeast': {'lat': 48.8436624802915,\n",
       "      'lng': 2.364700930291502},\n",
       "     'southwest': {'lat': 48.8409645197085, 'lng': 2.362002969708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Libertel Austerlitz Jardin des Plantes',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 4480,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/114802271282641766772\">Hôtel Libertel Austerlitz Jardin des Plantes</a>'],\n",
       "     'photo_reference': 'Aap_uED8R1KBIr9piwYPiO3glf07vU9WwTbrvAmAz7TJEfOstVrn50Z2PmcKJub-_2UFSz_hrG9KBCo1QQdVA8nQq7hHhBsH1pw8sF4aUs_job4I3FNnZf44ybVGZBeyXRZ3gOVzauTIiwWWBOGMLMTTMeV_5F4xt5AowIpCjl2XSw-Jjaxs',\n",
       "     'width': 6720}],\n",
       "   'place_id': 'ChIJe-udXPZx5kcRKURHNFv5BSw',\n",
       "   'plus_code': {'compound_code': 'R9R7+W7 Paris, France',\n",
       "    'global_code': '8FW4R9R7+W7'},\n",
       "   'rating': 3.9,\n",
       "   'reference': 'ChIJe-udXPZx5kcRKURHNFv5BSw',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 452,\n",
       "   'vicinity': \"12 Boulevard de l'Hôpital, Paris\"},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8642974, 'lng': 2.3308142},\n",
       "    'viewport': {'northeast': {'lat': 48.8655789302915,\n",
       "      'lng': 2.332153980291502},\n",
       "     'southwest': {'lat': 48.8628809697085, 'lng': 2.329456019708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Saint James Albany Paris Hôtel Spa',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 400,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/108570400659068256718\">Saint James Albany Paris Hôtel Spa</a>'],\n",
       "     'photo_reference': 'Aap_uEBbZWYmmDh53EndGH6dTOIEhfHCuh5KYcALNScr7aO19Cd6shacFh4psvwcJmo9E310FfxiMOsqGXiwKWP9PusbDDxlxRsqnj5klbXP3SD6neex7G0_QB4ao9oLsu0nMJrGsgwuLvU4QUFM_j8Hiyl1AOAq_mlKmZE2lnCUTF_NbBrA',\n",
       "     'width': 600}],\n",
       "   'place_id': 'ChIJ8znTVS5u5kcREq8TmzOICFs',\n",
       "   'plus_code': {'compound_code': 'V87J+P8 Paris, France',\n",
       "    'global_code': '8FW4V87J+P8'},\n",
       "   'rating': 4,\n",
       "   'reference': 'ChIJ8znTVS5u5kcREq8TmzOICFs',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging',\n",
       "    'bar',\n",
       "    'restaurant',\n",
       "    'food',\n",
       "    'point_of_interest',\n",
       "    'establishment'],\n",
       "   'user_ratings_total': 1074,\n",
       "   'vicinity': '202 Rue de Rivoli, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.87110329999999, 'lng': 2.3389728},\n",
       "    'viewport': {'northeast': {'lat': 48.8724169302915,\n",
       "      'lng': 2.340369280291502},\n",
       "     'southwest': {'lat': 48.8697189697085, 'lng': 2.337671319708499}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Icône',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 1066,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/108137830440312077288\">Hôtel Icône</a>'],\n",
       "     'photo_reference': 'Aap_uEALZ_esaNF9TtLBn334sUwINVqcbRXF37fPQwL_g6TgTAXP1C3vFJ1hFxYEn7IxKbEM_AbgPpoPjNaWgEoiE8ZWXOzusBTB77DnityHcoFuLb3Se3m-Z_IV_mRJhL4CO_51RYTPtbgcoajmNcT7je_MvPAEmeMXbX9xHDfeJSU7-_ya',\n",
       "     'width': 1600}],\n",
       "   'place_id': 'ChIJpQvq5Dtu5kcR0COam2f7v_I',\n",
       "   'plus_code': {'compound_code': 'V8CQ+CH Paris, France',\n",
       "    'global_code': '8FW4V8CQ+CH'},\n",
       "   'rating': 3.7,\n",
       "   'reference': 'ChIJpQvq5Dtu5kcR0COam2f7v_I',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 143,\n",
       "   'vicinity': \"4 Rue d'Amboise, Paris\"},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8524547, 'lng': 2.3472064},\n",
       "    'viewport': {'northeast': {'lat': 48.8538838802915,\n",
       "      'lng': 2.348601530291502},\n",
       "     'southwest': {'lat': 48.8511859197085, 'lng': 2.345903569708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel Esmeralda',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 1960,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/106443224837840180239\">Fraz A. Khan</a>'],\n",
       "     'photo_reference': 'Aap_uEChsIy7jIEFyBkQZg5Iy94T9vEpkn_-_21Pz-JsFMjBLb-kdHYch1tSNUcbQPO0_9XaBt77V9_YYAjq8GAcOWQqxAIrnePe2_MqeMwwWPqqooHf835rIKHM5T1yJ23jZH2aunHGzay3UJyn9MfY1BQWDdLH-VtoKlj0UeYtP4Cz779H',\n",
       "     'width': 4032}],\n",
       "   'place_id': 'ChIJO_g_H-Fx5kcRmaabUHA3dT4',\n",
       "   'plus_code': {'compound_code': 'V82W+XV Paris, France',\n",
       "    'global_code': '8FW4V82W+XV'},\n",
       "   'rating': 4.1,\n",
       "   'reference': 'ChIJO_g_H-Fx5kcRmaabUHA3dT4',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 152,\n",
       "   'vicinity': '4 Rue Saint-Julien le Pauvre, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8530901, 'lng': 2.3447174},\n",
       "    'viewport': {'northeast': {'lat': 48.8544535802915,\n",
       "      'lng': 2.345997680291501},\n",
       "     'southwest': {'lat': 48.85175561970851, 'lng': 2.343299719708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Albe Hotel',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 1152,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/117571951379278191466\">Albe Hotel Saint Michel</a>'],\n",
       "     'photo_reference': 'Aap_uEBfrnyD3cCOe4dA20jqzGIoiPO0oNTsEBqWD56M1j6_g0qxMNkcmtJcs-UXvDxA2dSJuixE8ydDtEFtpItwj3IExpgYE9QaqosIp9UnaSf6lSFVJd9aetG8uvwtyGHLWeuLk9afGPQhZPVCZpP4VbY86NrhDc_HPf3Rgz18V-SVt8Qh',\n",
       "     'width': 1600}],\n",
       "   'place_id': 'ChIJ8R5-hOBx5kcRsCOdfj8GLeY',\n",
       "   'plus_code': {'compound_code': 'V83V+6V Paris, France',\n",
       "    'global_code': '8FW4V83V+6V'},\n",
       "   'rating': 4.4,\n",
       "   'reference': 'ChIJ8R5-hOBx5kcRsCOdfj8GLeY',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 338,\n",
       "   'vicinity': '1 Rue de la Harpe, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8499446, 'lng': 2.346247699999999},\n",
       "    'viewport': {'northeast': {'lat': 48.8513264802915,\n",
       "      'lng': 2.347622530291501},\n",
       "     'southwest': {'lat': 48.8486285197085, 'lng': 2.344924569708497}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Home Latin',\n",
       "   'photos': [{'height': 606,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/105830788751825835396\">Peter Sheehan</a>'],\n",
       "     'photo_reference': 'Aap_uEDXDUiEMYCV_-9RzRhfwrYEzzFG6StGWzi4wJTh5aqo7GPQJZDVqTzN7_NSgBT4lPVobszINjOZPTb77c4GXlt6ITi0Lhyj1BTUjGuWW_GVjIZpqK7fcZ5b4pj97nVJ_mzRcDj1NujUool21rvji7CvCbydLiBUg1hY3cnvDxIknUyE',\n",
       "     'width': 1080}],\n",
       "   'place_id': 'ChIJMWNDIudx5kcRupjNdNDYKkw',\n",
       "   'plus_code': {'compound_code': 'R8XW+XF Paris, France',\n",
       "    'global_code': '8FW4R8XW+XF'},\n",
       "   'rating': 3.5,\n",
       "   'reference': 'ChIJMWNDIudx5kcRupjNdNDYKkw',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 294,\n",
       "   'vicinity': '15-17 Rue du Sommerard, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.8547358, 'lng': 2.3395366},\n",
       "    'viewport': {'northeast': {'lat': 48.8561113302915,\n",
       "      'lng': 2.340816080291502},\n",
       "     'southwest': {'lat': 48.85341336970851, 'lng': 2.338118119708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': \"Hôtel d'Aubusson\",\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 3568,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/115702439863948549296\">Hôtel d&#39;Aubusson Paris</a>'],\n",
       "     'photo_reference': 'Aap_uEBqH4xnguOxSF2tL55eohNgu3piV776ICSqLGSPDk78zkogCl0-91PrjvIzp6QmIbvXpqrB5R0hJK4Xn8bZZ2xoXZnPFLJtdpb2Pv5Bl375GRAAI8DdD5tYJQ448LEBjZP0wz6TnK3oVweKZD-2RiEkhrPq2f80ApcjMKXIW7cWaAWb',\n",
       "     'width': 5353}],\n",
       "   'place_id': 'ChIJk6ztMN9x5kcREpQ8edWOs7E',\n",
       "   'plus_code': {'compound_code': 'V83Q+VR Paris, France',\n",
       "    'global_code': '8FW4V83Q+VR'},\n",
       "   'rating': 4.7,\n",
       "   'reference': 'ChIJk6ztMN9x5kcREpQ8edWOs7E',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 302,\n",
       "   'vicinity': '33 Rue Dauphine, Paris'},\n",
       "  {'business_status': 'OPERATIONAL',\n",
       "   'geometry': {'location': {'lat': 48.85184049999999, 'lng': 2.3448082},\n",
       "    'viewport': {'northeast': {'lat': 48.8531470802915,\n",
       "      'lng': 2.346121880291502},\n",
       "     'southwest': {'lat': 48.8504491197085, 'lng': 2.343423919708498}}},\n",
       "   'icon': 'https://maps.gstatic.com/mapfiles/place_api/icons/v1/png_71/lodging-71.png',\n",
       "   'icon_background_color': '#909CE1',\n",
       "   'icon_mask_base_uri': 'https://maps.gstatic.com/mapfiles/place_api/icons/v2/hotel_pinlet',\n",
       "   'name': 'Hôtel 4 étoiles Parc Saint Séverin Paris 5ème - Esprit de France',\n",
       "   'opening_hours': {'open_now': True},\n",
       "   'photos': [{'height': 2362,\n",
       "     'html_attributions': ['<a href=\"https://maps.google.com/maps/contrib/107542132357877294567\">Hôtel 4 étoiles Parc Saint Séverin Paris 5ème - Esprit de France</a>'],\n",
       "     'photo_reference': 'Aap_uEBpIMiin2Enbw5oeNs-LC4cCcfXEPejLrBvSQuqelxIOcVeVb8a1yQo7d07WgHpI2fdWxpclm1YncNKH4AVLv4j_H9qFgf_Aivmya7ce7ParZYaLyj9Ix5dVHq1ozRWa-fZhMChpbfq6rv8en_5SX9iDVJno-T-vawwdd46zHu_7WBG',\n",
       "     'width': 3776}],\n",
       "   'place_id': 'ChIJ9--kuuBx5kcRojwQ1yEK2cY',\n",
       "   'plus_code': {'compound_code': 'V82V+PW Paris, France',\n",
       "    'global_code': '8FW4V82V+PW'},\n",
       "   'rating': 4.6,\n",
       "   'reference': 'ChIJ9--kuuBx5kcRojwQ1yEK2cY',\n",
       "   'scope': 'GOOGLE',\n",
       "   'types': ['lodging', 'point_of_interest', 'establishment'],\n",
       "   'user_ratings_total': 148,\n",
       "   'vicinity': '22 Rue de la Parcheminerie, Paris'}],\n",
       " 'status': 'OK'}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set parameters to search for a hotel.\n",
    "params = {\n",
    "    \"radius\": 5000,\n",
    "    \"type\": \"lodging\",\n",
    "    \"key\": g_key\n",
    "}\n",
    "\n",
    "# Dependencies and Setup\n",
    "import requests\n",
    "import gmaps\n",
    "\n",
    "# Import API key\n",
    "from config import g_key\n",
    "\n",
    "# Set the parameters to search for a hotel in Paris.\n",
    "params = {\n",
    "    \"radius\": 5000,\n",
    "    \"types\": \"lodging\",\n",
    "    \"key\": g_key,\n",
    "    \"location\": \"48.8566, 2.3522\"}\n",
    "# Use base URL to search for hotels in Paris.\n",
    "base_url = \"https://maps.googleapis.com/maps/api/place/nearbysearch/json\"\n",
    "# Make request and get the JSON data from the search.\n",
    "hotels = requests.get(base_url, params=params).json()\n",
    "\n",
    "hotels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cf7f93c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(hotels[\"results\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3870f67c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hôtel Duo'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotels[\"results\"][0][\"name\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "406bddc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n",
      "Hotel not found... skipping.\n"
     ]
    }
   ],
   "source": [
    "# Iterate through the DataFrame.\n",
    "for index, row in hotel_df.iterrows():\n",
    "    # Get the latitude and longitude.\n",
    "    lat = row[\"Lat\"]\n",
    "    lng = row[\"Lng\"]\n",
    "\n",
    "    # Add the latitude and longitude to location key for the params dictionary.\n",
    "    params[\"location\"] = f\"{lat},{lng}\"\n",
    "\n",
    "    # Use the search term: \"lodging\" and our latitude and longitude.\n",
    "    base_url = \"https://maps.googleapis.com/maps/api/place/nearbysearch/json\"\n",
    "    # Make request and get the JSON data from the search.\n",
    "    hotels = requests.get(base_url, params=params).json()\n",
    "    # Grab the first hotel from the results and store the name.\n",
    "    try:\n",
    "        hotel_df.loc[index, \"Hotel Name\"] = hotels[\"results\"][0][\"name\"]\n",
    "    except (IndexError):\n",
    "        print(\"Hotel not found... skipping.\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c8abf171",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "45e7edf2986d49d09537ca1166412e45",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add a heatmap of temperature for the vacation spots.\n",
    "locations = hotel_df[[\"Lat\", \"Lng\"]]\n",
    "max_temp = hotel_df[\"Max Temp\"]\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=max_temp, dissipating=False,\n",
    "             max_intensity=300, point_radius=4)\n",
    "\n",
    "fig.add_layer(heat_layer)\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cb72f6ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5c21f9299bcc447c8f3ded04dc34c1d7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add a heatmap of temperature for the vacation spots and marker for each city.\n",
    "locations = hotel_df[[\"Lat\", \"Lng\"]]\n",
    "max_temp = hotel_df[\"Max Temp\"]\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=max_temp,\n",
    "             dissipating=False, max_intensity=300, point_radius=4)\n",
    "marker_layer = gmaps.marker_layer(locations)\n",
    "fig.add_layer(heat_layer)\n",
    "fig.add_layer(marker_layer)\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d9ed1533",
   "metadata": {},
   "outputs": [],
   "source": [
    "info_box_template = \"\"\"\n",
    "<dl>\n",
    "<dt>Hotel Name</dt><dd>{Hotel Name}</dd>\n",
    "<dt>City</dt><dd>{City}</dd>\n",
    "<dt>Country</dt><dd>{Country}</dd>\n",
    "<dt>Max Temp</dt><dd>{Max Temp} °F</dd>\n",
    "</dl>\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "68fbdafd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store the DataFrame Row.\n",
    "hotel_info = [info_box_template.format(**row) for index, row in hotel_df.iterrows()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7ef988b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "300b48e1458b4a26977e968abb25259b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add a heatmap of temperature for the vacation spots and a pop-up marker for each city.\n",
    "locations = hotel_df[[\"Lat\", \"Lng\"]]\n",
    "max_temp = hotel_df[\"Max Temp\"]\n",
    "fig = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=max_temp,dissipating=False,\n",
    "             max_intensity=300, point_radius=4)\n",
    "marker_layer = gmaps.marker_layer(locations, info_box_content=hotel_info)\n",
    "fig.add_layer(heat_layer)\n",
    "fig.add_layer(marker_layer)\n",
    "\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "055412c5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}