VacationPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6df04a9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the dependencies.\n",
    "import pandas as pd\n",
    "import gmaps\n",
    "import requests\n",
    "\n",
    "#Import the api key\n",
    "from config import g_key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5b55284d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</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>Country</th>\n",
       "      <th>Date</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Beloha</td>\n",
       "      <td>MG</td>\n",
       "      <td>2021-07-29 14:47:56</td>\n",
       "      <td>-25.1667</td>\n",
       "      <td>45.0500</td>\n",
       "      <td>71.49</td>\n",
       "      <td>65</td>\n",
       "      <td>2</td>\n",
       "      <td>11.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Esperance</td>\n",
       "      <td>AU</td>\n",
       "      <td>2021-07-29 14:47:56</td>\n",
       "      <td>-33.8667</td>\n",
       "      <td>121.9000</td>\n",
       "      <td>58.84</td>\n",
       "      <td>72</td>\n",
       "      <td>27</td>\n",
       "      <td>24.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Hermanus</td>\n",
       "      <td>ZA</td>\n",
       "      <td>2021-07-29 14:47:56</td>\n",
       "      <td>-34.4187</td>\n",
       "      <td>19.2345</td>\n",
       "      <td>59.81</td>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>7.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Middletown</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-07-29 14:46:56</td>\n",
       "      <td>39.5151</td>\n",
       "      <td>-84.3983</td>\n",
       "      <td>81.75</td>\n",
       "      <td>85</td>\n",
       "      <td>1</td>\n",
       "      <td>10.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Chokurdakh</td>\n",
       "      <td>RU</td>\n",
       "      <td>2021-07-29 14:47:57</td>\n",
       "      <td>70.6333</td>\n",
       "      <td>147.9167</td>\n",
       "      <td>35.15</td>\n",
       "      <td>77</td>\n",
       "      <td>100</td>\n",
       "      <td>5.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City_ID        City Country                 Date      Lat       Lng  \\\n",
       "0        0      Beloha      MG  2021-07-29 14:47:56 -25.1667   45.0500   \n",
       "1        1   Esperance      AU  2021-07-29 14:47:56 -33.8667  121.9000   \n",
       "2        2    Hermanus      ZA  2021-07-29 14:47:56 -34.4187   19.2345   \n",
       "3        3  Middletown      US  2021-07-29 14:46:56  39.5151  -84.3983   \n",
       "4        4  Chokurdakh      RU  2021-07-29 14:47:57  70.6333  147.9167   \n",
       "\n",
       "   Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "0     71.49        65           2       11.83  \n",
       "1     58.84        72          27       24.79  \n",
       "2     59.81        79          79        7.54  \n",
       "3     81.75        85           1       10.36  \n",
       "4     35.15        77         100        5.97  "
      ]
     },
     "execution_count": 3,
     "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": 4,
   "id": "a32aad49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID         int64\n",
       "City           object\n",
       "Country        object\n",
       "Date           object\n",
       "Lat           float64\n",
       "Lng           float64\n",
       "Max Temp      float64\n",
       "Humidity        int64\n",
       "Cloudiness      int64\n",
       "Wind Speed    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data_df.dtypes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3477f453",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure gmaps to use your Google API key.\n",
    "gmaps.configure(api_key=g_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "695d01c4",
   "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": "203266ae",
   "metadata": {},
   "outputs": [
    {
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      },
      "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",
    "# 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, dissipating=False, max_intensity=300, point_radius=4)\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": 8,
   "id": "f28505fb",
   "metadata": {},
   "outputs": [
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   ],
   "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": 9,
   "id": "cd00a0bb",
   "metadata": {},
   "outputs": [
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   ],
   "source": [
    "# Heatmap of percent Cloudiness\n",
    "\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": 10,
   "id": "32e695af",
   "metadata": {},
   "outputs": [
    {
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   ],
   "source": [
    "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": 13,
   "id": "32eb3bf5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What is the minimum temperature you would like for your trip? 60\n",
      "What is the maximum temperature you would like for your trip? 90\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": 15,
   "id": "d1733a10",
   "metadata": {},
   "outputs": [
    {
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       "<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>Country</th>\n",
       "      <th>Date</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Beloha</td>\n",
       "      <td>MG</td>\n",
       "      <td>2021-07-29 14:47:56</td>\n",
       "      <td>-25.1667</td>\n",
       "      <td>45.0500</td>\n",
       "      <td>71.49</td>\n",
       "      <td>65</td>\n",
       "      <td>2</td>\n",
       "      <td>11.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Middletown</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-07-29 14:46:56</td>\n",
       "      <td>39.5151</td>\n",
       "      <td>-84.3983</td>\n",
       "      <td>81.75</td>\n",
       "      <td>85</td>\n",
       "      <td>1</td>\n",
       "      <td>10.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Saskylakh</td>\n",
       "      <td>RU</td>\n",
       "      <td>2021-07-29 14:47:57</td>\n",
       "      <td>71.9167</td>\n",
       "      <td>114.0833</td>\n",
       "      <td>72.57</td>\n",
       "      <td>58</td>\n",
       "      <td>31</td>\n",
       "      <td>7.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>2021-07-29 14:47:58</td>\n",
       "      <td>-23.1203</td>\n",
       "      <td>-134.9692</td>\n",
       "      <td>72.30</td>\n",
       "      <td>81</td>\n",
       "      <td>50</td>\n",
       "      <td>11.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>ZA</td>\n",
       "      <td>2021-07-29 14:43:23</td>\n",
       "      <td>-33.9258</td>\n",
       "      <td>18.4232</td>\n",
       "      <td>60.12</td>\n",
       "      <td>89</td>\n",
       "      <td>75</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Port Elizabeth</td>\n",
       "      <td>ZA</td>\n",
       "      <td>2021-07-29 14:47:58</td>\n",
       "      <td>-33.9180</td>\n",
       "      <td>25.5701</td>\n",
       "      <td>62.89</td>\n",
       "      <td>67</td>\n",
       "      <td>75</td>\n",
       "      <td>19.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>Yellowknife</td>\n",
       "      <td>CA</td>\n",
       "      <td>2021-07-29 14:47:59</td>\n",
       "      <td>62.4560</td>\n",
       "      <td>-114.3525</td>\n",
       "      <td>61.32</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>1.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>Grants</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-07-29 14:48:00</td>\n",
       "      <td>35.1473</td>\n",
       "      <td>-107.8514</td>\n",
       "      <td>66.43</td>\n",
       "      <td>77</td>\n",
       "      <td>75</td>\n",
       "      <td>3.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>Arraial Do Cabo</td>\n",
       "      <td>BR</td>\n",
       "      <td>2021-07-29 14:46:46</td>\n",
       "      <td>-22.9661</td>\n",
       "      <td>-42.0278</td>\n",
       "      <td>71.56</td>\n",
       "      <td>59</td>\n",
       "      <td>40</td>\n",
       "      <td>28.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>Avarua</td>\n",
       "      <td>CK</td>\n",
       "      <td>2021-07-29 14:48:01</td>\n",
       "      <td>-21.2078</td>\n",
       "      <td>-159.7750</td>\n",
       "      <td>66.25</td>\n",
       "      <td>94</td>\n",
       "      <td>33</td>\n",
       "      <td>3.44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    City_ID             City Country                 Date      Lat       Lng  \\\n",
       "0         0           Beloha      MG  2021-07-29 14:47:56 -25.1667   45.0500   \n",
       "3         3       Middletown      US  2021-07-29 14:46:56  39.5151  -84.3983   \n",
       "5         5        Saskylakh      RU  2021-07-29 14:47:57  71.9167  114.0833   \n",
       "7         7          Rikitea      PF  2021-07-29 14:47:58 -23.1203 -134.9692   \n",
       "8         8        Cape Town      ZA  2021-07-29 14:43:23 -33.9258   18.4232   \n",
       "9         9   Port Elizabeth      ZA  2021-07-29 14:47:58 -33.9180   25.5701   \n",
       "12       12      Yellowknife      CA  2021-07-29 14:47:59  62.4560 -114.3525   \n",
       "14       14           Grants      US  2021-07-29 14:48:00  35.1473 -107.8514   \n",
       "16       16  Arraial Do Cabo      BR  2021-07-29 14:46:46 -22.9661  -42.0278   \n",
       "17       17           Avarua      CK  2021-07-29 14:48:01 -21.2078 -159.7750   \n",
       "\n",
       "    Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "0      71.49        65           2       11.83  \n",
       "3      81.75        85           1       10.36  \n",
       "5      72.57        58          31        7.16  \n",
       "7      72.30        81          50       11.32  \n",
       "8      60.12        89          75        1.01  \n",
       "9      62.89        67          75       19.57  \n",
       "12     61.32       100          75        1.99  \n",
       "14     66.43        77          75        3.44  \n",
       "16     71.56        59          40       28.77  \n",
       "17     66.25        94          33        3.44  "
      ]
     },
     "execution_count": 15,
     "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": 16,
   "id": "7a3549ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       371\n",
       "City          371\n",
       "Country       367\n",
       "Date          371\n",
       "Lat           371\n",
       "Lng           371\n",
       "Max Temp      371\n",
       "Humidity      371\n",
       "Cloudiness    371\n",
       "Wind Speed    371\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "32a91c3e",
   "metadata": {},
   "outputs": [
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       "\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>0</th>\n",
       "      <td>Beloha</td>\n",
       "      <td>MG</td>\n",
       "      <td>71.49</td>\n",
       "      <td>-25.1667</td>\n",
       "      <td>45.0500</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Middletown</td>\n",
       "      <td>US</td>\n",
       "      <td>81.75</td>\n",
       "      <td>39.5151</td>\n",
       "      <td>-84.3983</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saskylakh</td>\n",
       "      <td>RU</td>\n",
       "      <td>72.57</td>\n",
       "      <td>71.9167</td>\n",
       "      <td>114.0833</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>72.30</td>\n",
       "      <td>-23.1203</td>\n",
       "      <td>-134.9692</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Cape Town</td>\n",
       "      <td>ZA</td>\n",
       "      <td>60.12</td>\n",
       "      <td>-33.9258</td>\n",
       "      <td>18.4232</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Port Elizabeth</td>\n",
       "      <td>ZA</td>\n",
       "      <td>62.89</td>\n",
       "      <td>-33.9180</td>\n",
       "      <td>25.5701</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Yellowknife</td>\n",
       "      <td>CA</td>\n",
       "      <td>61.32</td>\n",
       "      <td>62.4560</td>\n",
       "      <td>-114.3525</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Grants</td>\n",
       "      <td>US</td>\n",
       "      <td>66.43</td>\n",
       "      <td>35.1473</td>\n",
       "      <td>-107.8514</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Arraial Do Cabo</td>\n",
       "      <td>BR</td>\n",
       "      <td>71.56</td>\n",
       "      <td>-22.9661</td>\n",
       "      <td>-42.0278</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Avarua</td>\n",
       "      <td>CK</td>\n",
       "      <td>66.25</td>\n",
       "      <td>-21.2078</td>\n",
       "      <td>-159.7750</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               City Country  Max Temp      Lat       Lng Hotel Name\n",
       "0            Beloha      MG     71.49 -25.1667   45.0500           \n",
       "3        Middletown      US     81.75  39.5151  -84.3983           \n",
       "5         Saskylakh      RU     72.57  71.9167  114.0833           \n",
       "7           Rikitea      PF     72.30 -23.1203 -134.9692           \n",
       "8         Cape Town      ZA     60.12 -33.9258   18.4232           \n",
       "9    Port Elizabeth      ZA     62.89 -33.9180   25.5701           \n",
       "12      Yellowknife      CA     61.32  62.4560 -114.3525           \n",
       "14           Grants      US     66.43  35.1473 -107.8514           \n",
       "16  Arraial Do Cabo      BR     71.56 -22.9661  -42.0278           \n",
       "17           Avarua      CK     66.25 -21.2078 -159.7750           "
      ]
     },
     "execution_count": 17,
     "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": 18,
   "id": "bb91e23d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set parameters to search for a hotel.\n",
    "params = {\n",
    "    \"radius\": 5000,\n",
    "    \"type\": \"lodging\",\n",
    "    \"key\": g_key\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "167b7792",
   "metadata": {},
   "outputs": [],
   "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",
    "    \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": 26,
   "id": "5f679eae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9a0bca5a05924cba8489fec521672a21",
       "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": 22,
   "id": "e655e9e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "898db138d63a4417a78d650b11826433",
       "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": 35,
   "id": "7762927f",
   "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": 36,
   "id": "a38925d8",
   "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": 37,
   "id": "e2ba8ba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "13cc5a56320c4ebd922b11cb2732ff80",
       "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": "c9b924e2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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