VacationPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the dependencies.\n",
    "import pandas as pd\n",
    "import gmaps\n",
    "import requests\n",
    "import numpy as np\n",
    "# Import the API key.\n",
    "from config import g_key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the Citipy module to determine city based on latitude and longitude\n",
    "from citipy import citipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "        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>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>Busselton</td>\n",
       "      <td>AU</td>\n",
       "      <td>2020-04-24 03:09:33</td>\n",
       "      <td>-33.65</td>\n",
       "      <td>115.33</td>\n",
       "      <td>70.00</td>\n",
       "      <td>51</td>\n",
       "      <td>26</td>\n",
       "      <td>12.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Hilo</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-04-24 03:08:44</td>\n",
       "      <td>19.73</td>\n",
       "      <td>-155.09</td>\n",
       "      <td>80.60</td>\n",
       "      <td>57</td>\n",
       "      <td>40</td>\n",
       "      <td>9.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Upernavik</td>\n",
       "      <td>GL</td>\n",
       "      <td>2020-04-24 03:09:33</td>\n",
       "      <td>72.79</td>\n",
       "      <td>-56.15</td>\n",
       "      <td>24.80</td>\n",
       "      <td>97</td>\n",
       "      <td>3</td>\n",
       "      <td>7.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Albany</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-04-24 03:05:46</td>\n",
       "      <td>42.60</td>\n",
       "      <td>-73.97</td>\n",
       "      <td>44.60</td>\n",
       "      <td>45</td>\n",
       "      <td>75</td>\n",
       "      <td>6.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>2020-04-24 03:09:34</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td>76.01</td>\n",
       "      <td>77</td>\n",
       "      <td>24</td>\n",
       "      <td>12.17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City_ID       City Country                 Date    Lat     Lng  Max Temp  \\\n",
       "0        0  Busselton      AU  2020-04-24 03:09:33 -33.65  115.33     70.00   \n",
       "1        1       Hilo      US  2020-04-24 03:08:44  19.73 -155.09     80.60   \n",
       "2        2  Upernavik      GL  2020-04-24 03:09:33  72.79  -56.15     24.80   \n",
       "3        3     Albany      US  2020-04-24 03:05:46  42.60  -73.97     44.60   \n",
       "4        4    Rikitea      PF  2020-04-24 03:09:34 -23.12 -134.97     76.01   \n",
       "\n",
       "   Humidity  Cloudiness  Wind Speed  \n",
       "0        51          26       12.44  \n",
       "1        57          40        9.17  \n",
       "2        97           3        7.78  \n",
       "3        45          75        6.93  \n",
       "4        77          24       12.17  "
      ]
     },
     "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,
   "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure gmaps to use your Google API key.\n",
    "gmaps.configure(api_key=g_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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,
   "metadata": {
    "scrolled": true
   },
   "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()\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": 8,
   "metadata": {},
   "outputs": [
    {
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       "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()\n",
    "# Assign the heatmap variable.\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=temps, 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 = gmaps.figure(center=(30.0, 31.0), zoom_level=1.5)\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "Figure(layout=FigureLayout(height='420px'))"
      ]
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     "metadata": {},
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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": 10,
   "metadata": {},
   "outputs": [
    {
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       "Figure(layout=FigureLayout(height='420px'))"
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     "metadata": {},
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    }
   ],
   "source": [
    "# Heatmap of percent Cloudiness\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": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap of percent Wind Speed\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": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What is the minimum temperature you would like for your trip? 75\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": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Hilo</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-04-24 03:08:44</td>\n",
       "      <td>19.73</td>\n",
       "      <td>-155.09</td>\n",
       "      <td>80.60</td>\n",
       "      <td>57</td>\n",
       "      <td>40</td>\n",
       "      <td>9.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>2020-04-24 03:09:34</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td>76.01</td>\n",
       "      <td>77</td>\n",
       "      <td>24</td>\n",
       "      <td>12.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Saint-Philippe</td>\n",
       "      <td>RE</td>\n",
       "      <td>2020-04-24 03:09:34</td>\n",
       "      <td>-21.36</td>\n",
       "      <td>55.77</td>\n",
       "      <td>75.20</td>\n",
       "      <td>88</td>\n",
       "      <td>20</td>\n",
       "      <td>10.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>Amahai</td>\n",
       "      <td>ID</td>\n",
       "      <td>2020-04-24 03:09:36</td>\n",
       "      <td>-3.33</td>\n",
       "      <td>128.92</td>\n",
       "      <td>87.57</td>\n",
       "      <td>63</td>\n",
       "      <td>13</td>\n",
       "      <td>3.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>Kui Buri</td>\n",
       "      <td>TH</td>\n",
       "      <td>2020-04-24 03:09:37</td>\n",
       "      <td>12.08</td>\n",
       "      <td>99.85</td>\n",
       "      <td>87.80</td>\n",
       "      <td>62</td>\n",
       "      <td>20</td>\n",
       "      <td>5.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    City_ID            City Country                 Date    Lat     Lng  \\\n",
       "1         1            Hilo      US  2020-04-24 03:08:44  19.73 -155.09   \n",
       "4         4         Rikitea      PF  2020-04-24 03:09:34 -23.12 -134.97   \n",
       "5         5  Saint-Philippe      RE  2020-04-24 03:09:34 -21.36   55.77   \n",
       "11       11          Amahai      ID  2020-04-24 03:09:36  -3.33  128.92   \n",
       "16       16        Kui Buri      TH  2020-04-24 03:09:37  12.08   99.85   \n",
       "\n",
       "    Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "1      80.60        57          40        9.17  \n",
       "4      76.01        77          24       12.17  \n",
       "5      75.20        88          20       10.29  \n",
       "11     87.57        63          13        3.87  \n",
       "16     87.80        62          20        5.82  "
      ]
     },
     "execution_count": 13,
     "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\"] <= 90) & \\\n",
    "                                       (city_data_df[\"Max Temp\"] >= 75)]\n",
    "preferred_cities_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       155\n",
       "City          155\n",
       "Country       155\n",
       "Date          155\n",
       "Lat           155\n",
       "Lng           155\n",
       "Max Temp      155\n",
       "Humidity      155\n",
       "Cloudiness    155\n",
       "Wind Speed    155\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<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>Hilo</td>\n",
       "      <td>US</td>\n",
       "      <td>80.60</td>\n",
       "      <td>19.73</td>\n",
       "      <td>-155.09</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>76.01</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saint-Philippe</td>\n",
       "      <td>RE</td>\n",
       "      <td>75.20</td>\n",
       "      <td>-21.36</td>\n",
       "      <td>55.77</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Amahai</td>\n",
       "      <td>ID</td>\n",
       "      <td>87.57</td>\n",
       "      <td>-3.33</td>\n",
       "      <td>128.92</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kui Buri</td>\n",
       "      <td>TH</td>\n",
       "      <td>87.80</td>\n",
       "      <td>12.08</td>\n",
       "      <td>99.85</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Alice Springs</td>\n",
       "      <td>AU</td>\n",
       "      <td>89.60</td>\n",
       "      <td>-23.70</td>\n",
       "      <td>133.88</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Gorom-Gorom</td>\n",
       "      <td>BF</td>\n",
       "      <td>87.60</td>\n",
       "      <td>14.44</td>\n",
       "      <td>-0.24</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Kapaa</td>\n",
       "      <td>US</td>\n",
       "      <td>80.60</td>\n",
       "      <td>22.08</td>\n",
       "      <td>-159.32</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Mitsamiouli</td>\n",
       "      <td>KM</td>\n",
       "      <td>82.18</td>\n",
       "      <td>-11.38</td>\n",
       "      <td>43.28</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Puerto Ayora</td>\n",
       "      <td>EC</td>\n",
       "      <td>79.00</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>-90.35</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Country  Max Temp    Lat     Lng Hotel Name\n",
       "1             Hilo      US     80.60  19.73 -155.09           \n",
       "4          Rikitea      PF     76.01 -23.12 -134.97           \n",
       "5   Saint-Philippe      RE     75.20 -21.36   55.77           \n",
       "11          Amahai      ID     87.57  -3.33  128.92           \n",
       "16        Kui Buri      TH     87.80  12.08   99.85           \n",
       "19   Alice Springs      AU     89.60 -23.70  133.88           \n",
       "25     Gorom-Gorom      BF     87.60  14.44   -0.24           \n",
       "26           Kapaa      US     80.60  22.08 -159.32           \n",
       "27     Mitsamiouli      KM     82.18 -11.38   43.28           \n",
       "31    Puerto Ayora      EC     79.00  -0.74  -90.35           "
      ]
     },
     "execution_count": 15,
     "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": 16,
   "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": 17,
   "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>Hilo</td>\n",
       "      <td>US</td>\n",
       "      <td>80.60</td>\n",
       "      <td>19.73</td>\n",
       "      <td>-155.09</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>76.01</td>\n",
       "      <td>-23.12</td>\n",
       "      <td>-134.97</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saint-Philippe</td>\n",
       "      <td>RE</td>\n",
       "      <td>75.20</td>\n",
       "      <td>-21.36</td>\n",
       "      <td>55.77</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Amahai</td>\n",
       "      <td>ID</td>\n",
       "      <td>87.57</td>\n",
       "      <td>-3.33</td>\n",
       "      <td>128.92</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kui Buri</td>\n",
       "      <td>TH</td>\n",
       "      <td>87.80</td>\n",
       "      <td>12.08</td>\n",
       "      <td>99.85</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Alice Springs</td>\n",
       "      <td>AU</td>\n",
       "      <td>89.60</td>\n",
       "      <td>-23.70</td>\n",
       "      <td>133.88</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Gorom-Gorom</td>\n",
       "      <td>BF</td>\n",
       "      <td>87.60</td>\n",
       "      <td>14.44</td>\n",
       "      <td>-0.24</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Kapaa</td>\n",
       "      <td>US</td>\n",
       "      <td>80.60</td>\n",
       "      <td>22.08</td>\n",
       "      <td>-159.32</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Mitsamiouli</td>\n",
       "      <td>KM</td>\n",
       "      <td>82.18</td>\n",
       "      <td>-11.38</td>\n",
       "      <td>43.28</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Puerto Ayora</td>\n",
       "      <td>EC</td>\n",
       "      <td>79.00</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>-90.35</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Country  Max Temp    Lat     Lng Hotel Name\n",
       "1             Hilo      US     80.60  19.73 -155.09           \n",
       "4          Rikitea      PF     76.01 -23.12 -134.97           \n",
       "5   Saint-Philippe      RE     75.20 -21.36   55.77           \n",
       "11          Amahai      ID     87.57  -3.33  128.92           \n",
       "16        Kui Buri      TH     87.80  12.08   99.85           \n",
       "19   Alice Springs      AU     89.60 -23.70  133.88           \n",
       "25     Gorom-Gorom      BF     87.60  14.44   -0.24           \n",
       "26           Kapaa      US     80.60  22.08 -159.32           \n",
       "27     Mitsamiouli      KM     82.18 -11.38   43.28           \n",
       "31    Puerto Ayora      EC     79.00  -0.74  -90.35           "
      ]
     },
     "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,
   "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",
    "try:\n",
    "    hotel_df.loc[index, \"Hotel Name\"] = hotels[\"results\"][0][\"name\"]\n",
    "except (IndexError):\n",
    "    print(\"Hotel not found... skipping.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "db850a86693943a2aedcc0745e0c5af0",
       "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",
    "# Add pop up markers\n",
    "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",
    "\"\"\"\n",
    "# Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9e0cdc91d725456d94db7615e919cd68",
       "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,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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