VacationPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d49ef699",
   "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": "b7bd75ce",
   "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>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>Sovetskiy</td>\n",
       "      <td>RU</td>\n",
       "      <td>2021-07-07 22:49:21</td>\n",
       "      <td>61.3614</td>\n",
       "      <td>63.5842</td>\n",
       "      <td>61.36</td>\n",
       "      <td>75</td>\n",
       "      <td>34</td>\n",
       "      <td>4.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Krasnoselkup</td>\n",
       "      <td>RU</td>\n",
       "      <td>2021-07-07 22:49:22</td>\n",
       "      <td>65.7000</td>\n",
       "      <td>82.4667</td>\n",
       "      <td>53.69</td>\n",
       "      <td>75</td>\n",
       "      <td>47</td>\n",
       "      <td>9.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Toowoomba</td>\n",
       "      <td>AU</td>\n",
       "      <td>2021-07-07 22:49:22</td>\n",
       "      <td>-27.5500</td>\n",
       "      <td>151.9667</td>\n",
       "      <td>52.25</td>\n",
       "      <td>75</td>\n",
       "      <td>22</td>\n",
       "      <td>3.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Vaini</td>\n",
       "      <td>TO</td>\n",
       "      <td>2021-07-07 22:49:22</td>\n",
       "      <td>-21.2000</td>\n",
       "      <td>-175.2000</td>\n",
       "      <td>77.16</td>\n",
       "      <td>69</td>\n",
       "      <td>20</td>\n",
       "      <td>14.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Alofi</td>\n",
       "      <td>NU</td>\n",
       "      <td>2021-07-07 22:49:23</td>\n",
       "      <td>-19.0595</td>\n",
       "      <td>-169.9187</td>\n",
       "      <td>76.89</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>14.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City_ID          City Country                 Date      Lat       Lng  \\\n",
       "0        0     Sovetskiy      RU  2021-07-07 22:49:21  61.3614   63.5842   \n",
       "1        1  Krasnoselkup      RU  2021-07-07 22:49:22  65.7000   82.4667   \n",
       "2        2     Toowoomba      AU  2021-07-07 22:49:22 -27.5500  151.9667   \n",
       "3        3         Vaini      TO  2021-07-07 22:49:22 -21.2000 -175.2000   \n",
       "4        4         Alofi      NU  2021-07-07 22:49:23 -19.0595 -169.9187   \n",
       "\n",
       "   Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "0     61.36        75          34        4.29  \n",
       "1     53.69        75          47        9.71  \n",
       "2     52.25        75          22        3.00  \n",
       "3     77.16        69          20       14.97  \n",
       "4     76.89        69          40       14.97  "
      ]
     },
     "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": "dffee81e",
   "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": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2e006433",
   "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": "94ca7fd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cfe149f5dc454b8a8ed927593e8ddfa1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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))\n",
    "# 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 = 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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f6be5f03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3cbd3a3156fb4d56967e53ab684a0684",
       "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": 7,
   "id": "5e3ba40d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "44e0440daad54220b5b5665faf19cf61",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 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": 8,
   "id": "f3b4d7ff",
   "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": 9,
   "id": "3f0e1c7a",
   "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>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>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Vaini</td>\n",
       "      <td>TO</td>\n",
       "      <td>2021-07-07 22:49:22</td>\n",
       "      <td>-21.2000</td>\n",
       "      <td>-175.2000</td>\n",
       "      <td>77.16</td>\n",
       "      <td>69</td>\n",
       "      <td>20</td>\n",
       "      <td>14.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Alofi</td>\n",
       "      <td>NU</td>\n",
       "      <td>2021-07-07 22:49:23</td>\n",
       "      <td>-19.0595</td>\n",
       "      <td>-169.9187</td>\n",
       "      <td>76.89</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>14.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Palu</td>\n",
       "      <td>ID</td>\n",
       "      <td>2021-07-07 22:49:23</td>\n",
       "      <td>-0.8917</td>\n",
       "      <td>119.8707</td>\n",
       "      <td>75.58</td>\n",
       "      <td>93</td>\n",
       "      <td>92</td>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Katsuura</td>\n",
       "      <td>JP</td>\n",
       "      <td>2021-07-07 22:49:23</td>\n",
       "      <td>35.1333</td>\n",
       "      <td>140.3000</td>\n",
       "      <td>77.11</td>\n",
       "      <td>91</td>\n",
       "      <td>100</td>\n",
       "      <td>9.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Acarau</td>\n",
       "      <td>BR</td>\n",
       "      <td>2021-07-07 22:49:24</td>\n",
       "      <td>-2.8856</td>\n",
       "      <td>-40.1200</td>\n",
       "      <td>78.21</td>\n",
       "      <td>79</td>\n",
       "      <td>43</td>\n",
       "      <td>9.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Kahului</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-07-07 22:48:29</td>\n",
       "      <td>20.8947</td>\n",
       "      <td>-156.4700</td>\n",
       "      <td>85.26</td>\n",
       "      <td>71</td>\n",
       "      <td>40</td>\n",
       "      <td>20.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>Mount Pleasant</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-07-07 22:49:25</td>\n",
       "      <td>32.7941</td>\n",
       "      <td>-79.8626</td>\n",
       "      <td>83.01</td>\n",
       "      <td>86</td>\n",
       "      <td>75</td>\n",
       "      <td>3.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>Hatillo</td>\n",
       "      <td>PR</td>\n",
       "      <td>2021-07-07 22:49:28</td>\n",
       "      <td>18.4863</td>\n",
       "      <td>-66.8254</td>\n",
       "      <td>86.38</td>\n",
       "      <td>77</td>\n",
       "      <td>90</td>\n",
       "      <td>20.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>Hobyo</td>\n",
       "      <td>SO</td>\n",
       "      <td>2021-07-07 22:49:30</td>\n",
       "      <td>5.3505</td>\n",
       "      <td>48.5268</td>\n",
       "      <td>76.32</td>\n",
       "      <td>78</td>\n",
       "      <td>20</td>\n",
       "      <td>23.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>Fort Nelson</td>\n",
       "      <td>CA</td>\n",
       "      <td>2021-07-07 22:46:34</td>\n",
       "      <td>58.8053</td>\n",
       "      <td>-122.7002</td>\n",
       "      <td>83.79</td>\n",
       "      <td>30</td>\n",
       "      <td>40</td>\n",
       "      <td>3.44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    City_ID            City Country                 Date      Lat       Lng  \\\n",
       "3         3           Vaini      TO  2021-07-07 22:49:22 -21.2000 -175.2000   \n",
       "4         4           Alofi      NU  2021-07-07 22:49:23 -19.0595 -169.9187   \n",
       "5         5            Palu      ID  2021-07-07 22:49:23  -0.8917  119.8707   \n",
       "6         6        Katsuura      JP  2021-07-07 22:49:23  35.1333  140.3000   \n",
       "8         8          Acarau      BR  2021-07-07 22:49:24  -2.8856  -40.1200   \n",
       "9         9         Kahului      US  2021-07-07 22:48:29  20.8947 -156.4700   \n",
       "11       11  Mount Pleasant      US  2021-07-07 22:49:25  32.7941  -79.8626   \n",
       "21       21         Hatillo      PR  2021-07-07 22:49:28  18.4863  -66.8254   \n",
       "26       26           Hobyo      SO  2021-07-07 22:49:30   5.3505   48.5268   \n",
       "31       31     Fort Nelson      CA  2021-07-07 22:46:34  58.8053 -122.7002   \n",
       "\n",
       "    Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "3      77.16        69          20       14.97  \n",
       "4      76.89        69          40       14.97  \n",
       "5      75.58        93          92        2.39  \n",
       "6      77.11        91         100        9.10  \n",
       "8      78.21        79          43        9.42  \n",
       "9      85.26        71          40       20.71  \n",
       "11     83.01        86          75        3.00  \n",
       "21     86.38        77          90       20.54  \n",
       "26     76.32        78          20       23.71  \n",
       "31     83.79        30          40        3.44  "
      ]
     },
     "execution_count": 9,
     "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": 12,
   "id": "768edb68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       199\n",
       "City          199\n",
       "Country       199\n",
       "Date          199\n",
       "Lat           199\n",
       "Lng           199\n",
       "Max Temp      199\n",
       "Humidity      199\n",
       "Cloudiness    199\n",
       "Wind Speed    199\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preferred_cities_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d8f9a778",
   "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>3</th>\n",
       "      <td>Vaini</td>\n",
       "      <td>TO</td>\n",
       "      <td>77.16</td>\n",
       "      <td>-21.2000</td>\n",
       "      <td>-175.2000</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alofi</td>\n",
       "      <td>NU</td>\n",
       "      <td>76.89</td>\n",
       "      <td>-19.0595</td>\n",
       "      <td>-169.9187</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Palu</td>\n",
       "      <td>ID</td>\n",
       "      <td>75.58</td>\n",
       "      <td>-0.8917</td>\n",
       "      <td>119.8707</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Katsuura</td>\n",
       "      <td>JP</td>\n",
       "      <td>77.11</td>\n",
       "      <td>35.1333</td>\n",
       "      <td>140.3000</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Acarau</td>\n",
       "      <td>BR</td>\n",
       "      <td>78.21</td>\n",
       "      <td>-2.8856</td>\n",
       "      <td>-40.1200</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Kahului</td>\n",
       "      <td>US</td>\n",
       "      <td>85.26</td>\n",
       "      <td>20.8947</td>\n",
       "      <td>-156.4700</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Mount Pleasant</td>\n",
       "      <td>US</td>\n",
       "      <td>83.01</td>\n",
       "      <td>32.7941</td>\n",
       "      <td>-79.8626</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Hatillo</td>\n",
       "      <td>PR</td>\n",
       "      <td>86.38</td>\n",
       "      <td>18.4863</td>\n",
       "      <td>-66.8254</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hobyo</td>\n",
       "      <td>SO</td>\n",
       "      <td>76.32</td>\n",
       "      <td>5.3505</td>\n",
       "      <td>48.5268</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Fort Nelson</td>\n",
       "      <td>CA</td>\n",
       "      <td>83.79</td>\n",
       "      <td>58.8053</td>\n",
       "      <td>-122.7002</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Country  Max Temp      Lat       Lng Hotel Name\n",
       "3            Vaini      TO     77.16 -21.2000 -175.2000           \n",
       "4            Alofi      NU     76.89 -19.0595 -169.9187           \n",
       "5             Palu      ID     75.58  -0.8917  119.8707           \n",
       "6         Katsuura      JP     77.11  35.1333  140.3000           \n",
       "8           Acarau      BR     78.21  -2.8856  -40.1200           \n",
       "9          Kahului      US     85.26  20.8947 -156.4700           \n",
       "11  Mount Pleasant      US     83.01  32.7941  -79.8626           \n",
       "21         Hatillo      PR     86.38  18.4863  -66.8254           \n",
       "26           Hobyo      SO     76.32   5.3505   48.5268           \n",
       "31     Fort Nelson      CA     83.79  58.8053 -122.7002           "
      ]
     },
     "execution_count": 13,
     "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": 14,
   "id": "aa43d10b",
   "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": 16,
   "id": "33b073c6",
   "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": 17,
   "id": "35a36b16",
   "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>3</th>\n",
       "      <td>Vaini</td>\n",
       "      <td>TO</td>\n",
       "      <td>77.16</td>\n",
       "      <td>-21.2000</td>\n",
       "      <td>-175.2000</td>\n",
       "      <td>Keleti Beach Resort</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alofi</td>\n",
       "      <td>NU</td>\n",
       "      <td>76.89</td>\n",
       "      <td>-19.0595</td>\n",
       "      <td>-169.9187</td>\n",
       "      <td>Taloa Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Palu</td>\n",
       "      <td>ID</td>\n",
       "      <td>75.58</td>\n",
       "      <td>-0.8917</td>\n",
       "      <td>119.8707</td>\n",
       "      <td>Hotel Santika Palu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Katsuura</td>\n",
       "      <td>JP</td>\n",
       "      <td>77.11</td>\n",
       "      <td>35.1333</td>\n",
       "      <td>140.3000</td>\n",
       "      <td>Katsuura Hotel Mikazuki</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Acarau</td>\n",
       "      <td>BR</td>\n",
       "      <td>78.21</td>\n",
       "      <td>-2.8856</td>\n",
       "      <td>-40.1200</td>\n",
       "      <td>castelo pizzaria</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       City Country  Max Temp      Lat       Lng               Hotel Name\n",
       "3     Vaini      TO     77.16 -21.2000 -175.2000      Keleti Beach Resort\n",
       "4     Alofi      NU     76.89 -19.0595 -169.9187            Taloa Heights\n",
       "5      Palu      ID     75.58  -0.8917  119.8707       Hotel Santika Palu\n",
       "6  Katsuura      JP     77.11  35.1333  140.3000  Katsuura Hotel Mikazuki\n",
       "8    Acarau      BR     78.21  -2.8856  -40.1200         castelo pizzaria"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotel_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b08300b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "277f92d4ab024dd8ba4bd75aa46e43e1",
       "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": 21,
   "id": "700949e1",
   "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",
    "\"\"\"\n",
    "# Store the DataFrame Row.\n",
    "hotel_info = [info_box_template.format(**row) for index, row in hotel_df.iterrows()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "15aec097",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "31134e013ca64be7996e720cb56c84d8",
       "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": "204f00f8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pydata",
   "language": "python",
   "name": "pydata"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}