VacationPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "93471c38",
   "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": 2,
   "id": "053a129a",
   "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>Tuktoyaktuk</td>\n",
       "      <td>CA</td>\n",
       "      <td>2021-12-30 16:26:11</td>\n",
       "      <td>69.4541</td>\n",
       "      <td>-133.0374</td>\n",
       "      <td>-20.20</td>\n",
       "      <td>76</td>\n",
       "      <td>90</td>\n",
       "      <td>4.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Tasiilaq</td>\n",
       "      <td>GL</td>\n",
       "      <td>2021-12-30 16:26:12</td>\n",
       "      <td>65.6145</td>\n",
       "      <td>-37.6368</td>\n",
       "      <td>10.56</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>4.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Laguna</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-12-30 16:26:12</td>\n",
       "      <td>38.4210</td>\n",
       "      <td>-121.4238</td>\n",
       "      <td>45.10</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>3.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Iowa City</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-12-30 16:25:02</td>\n",
       "      <td>41.6611</td>\n",
       "      <td>-91.5302</td>\n",
       "      <td>28.69</td>\n",
       "      <td>88</td>\n",
       "      <td>90</td>\n",
       "      <td>8.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Mar Del Plata</td>\n",
       "      <td>AR</td>\n",
       "      <td>2021-12-30 16:25:36</td>\n",
       "      <td>-38.0023</td>\n",
       "      <td>-57.5575</td>\n",
       "      <td>86.02</td>\n",
       "      <td>49</td>\n",
       "      <td>75</td>\n",
       "      <td>1.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City_ID           City Country                 Date      Lat       Lng  \\\n",
       "0        0    Tuktoyaktuk      CA  2021-12-30 16:26:11  69.4541 -133.0374   \n",
       "1        1       Tasiilaq      GL  2021-12-30 16:26:12  65.6145  -37.6368   \n",
       "2        2         Laguna      US  2021-12-30 16:26:12  38.4210 -121.4238   \n",
       "3        3      Iowa City      US  2021-12-30 16:25:02  41.6611  -91.5302   \n",
       "4        4  Mar Del Plata      AR  2021-12-30 16:25:36 -38.0023  -57.5575   \n",
       "\n",
       "   Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "0    -20.20        76          90        4.61  \n",
       "1     10.56        55           0        4.90  \n",
       "2     45.10        90          90        3.00  \n",
       "3     28.69        88          90        8.05  \n",
       "4     86.02        49          75        1.99  "
      ]
     },
     "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": "1c5b681a",
   "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": [
    "# Get the data types.\n",
    "city_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aadd63ba",
   "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": "d339babb",
   "metadata": {},
   "outputs": [
    {
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       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The general syntax for creating a heatmap is as follows.\n",
    "# Heatmap of temperature\n",
    "# 1 Get the latitude and longitude.\n",
    "locations = city_data_df[[\"Lat\", \"Lng\"]]\n",
    "\n",
    "# 2 Assign the weights variable to some values.\n",
    "# Get the maximum temperature.\n",
    "max_temp = city_data_df[\"Max Temp\"]\n",
    "\n",
    "# 3 configure the gmap\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 \n",
    "# add in the locations.\n",
    "heat_layer = gmaps.heatmap_layer(locations, weights=[max(temp, 0) for temp in max_temp],\n",
    "                                 dissipating=False, max_intensity=300, point_radius=4)\n",
    "\n",
    "# 5 Add the heatmap layer.\n",
    "fig.add_layer(heat_layer)\n",
    "\n",
    "# 6 Call the figure to plot the data.\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "36f7181a",
   "metadata": {},
   "outputs": [
    {
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       "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": "4c925cf9",
   "metadata": {},
   "outputs": [
    {
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       "model_id": "cf02b54e56864daaba2c2260eacb41a4",
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       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap of 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": 8,
   "id": "71df6ca8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "59fdbbe5301d4b4896953832608d2831",
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      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap of 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": 9,
   "id": "270c1983",
   "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": 10,
   "id": "dfefc89c",
   "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>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Mar Del Plata</td>\n",
       "      <td>AR</td>\n",
       "      <td>2021-12-30 16:25:36</td>\n",
       "      <td>-38.0023</td>\n",
       "      <td>-57.5575</td>\n",
       "      <td>86.02</td>\n",
       "      <td>49</td>\n",
       "      <td>75</td>\n",
       "      <td>1.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Cabo San Lucas</td>\n",
       "      <td>MX</td>\n",
       "      <td>2021-12-30 16:23:14</td>\n",
       "      <td>22.8909</td>\n",
       "      <td>-109.9124</td>\n",
       "      <td>75.51</td>\n",
       "      <td>80</td>\n",
       "      <td>88</td>\n",
       "      <td>3.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Salinopolis</td>\n",
       "      <td>BR</td>\n",
       "      <td>2021-12-30 16:26:14</td>\n",
       "      <td>-0.6136</td>\n",
       "      <td>-47.3561</td>\n",
       "      <td>81.86</td>\n",
       "      <td>81</td>\n",
       "      <td>83</td>\n",
       "      <td>9.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>Namatanai</td>\n",
       "      <td>PG</td>\n",
       "      <td>2021-12-30 16:26:14</td>\n",
       "      <td>-3.6667</td>\n",
       "      <td>152.4333</td>\n",
       "      <td>81.32</td>\n",
       "      <td>80</td>\n",
       "      <td>96</td>\n",
       "      <td>6.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>Broken Hill</td>\n",
       "      <td>AU</td>\n",
       "      <td>2021-12-30 16:24:18</td>\n",
       "      <td>-31.9500</td>\n",
       "      <td>141.4333</td>\n",
       "      <td>77.54</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>7.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>Puerto Ayora</td>\n",
       "      <td>EC</td>\n",
       "      <td>2021-12-30 16:26:16</td>\n",
       "      <td>-0.7393</td>\n",
       "      <td>-90.3518</td>\n",
       "      <td>78.76</td>\n",
       "      <td>79</td>\n",
       "      <td>94</td>\n",
       "      <td>10.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>Georgetown</td>\n",
       "      <td>MY</td>\n",
       "      <td>2021-12-30 16:21:36</td>\n",
       "      <td>5.4112</td>\n",
       "      <td>100.3354</td>\n",
       "      <td>80.89</td>\n",
       "      <td>86</td>\n",
       "      <td>40</td>\n",
       "      <td>5.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>Mahebourg</td>\n",
       "      <td>MU</td>\n",
       "      <td>2021-12-30 16:26:20</td>\n",
       "      <td>-20.4081</td>\n",
       "      <td>57.7000</td>\n",
       "      <td>78.26</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>10.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>32</td>\n",
       "      <td>Mogadishu</td>\n",
       "      <td>SO</td>\n",
       "      <td>2021-12-30 16:26:21</td>\n",
       "      <td>2.0371</td>\n",
       "      <td>45.3438</td>\n",
       "      <td>78.21</td>\n",
       "      <td>74</td>\n",
       "      <td>85</td>\n",
       "      <td>19.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>33</td>\n",
       "      <td>Thinadhoo</td>\n",
       "      <td>MV</td>\n",
       "      <td>2021-12-30 16:26:21</td>\n",
       "      <td>0.5333</td>\n",
       "      <td>72.9333</td>\n",
       "      <td>81.36</td>\n",
       "      <td>76</td>\n",
       "      <td>62</td>\n",
       "      <td>12.66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    City_ID            City Country                 Date      Lat       Lng  \\\n",
       "4         4   Mar Del Plata      AR  2021-12-30 16:25:36 -38.0023  -57.5575   \n",
       "6         6  Cabo San Lucas      MX  2021-12-30 16:23:14  22.8909 -109.9124   \n",
       "9         9     Salinopolis      BR  2021-12-30 16:26:14  -0.6136  -47.3561   \n",
       "10       10       Namatanai      PG  2021-12-30 16:26:14  -3.6667  152.4333   \n",
       "13       13     Broken Hill      AU  2021-12-30 16:24:18 -31.9500  141.4333   \n",
       "15       15    Puerto Ayora      EC  2021-12-30 16:26:16  -0.7393  -90.3518   \n",
       "17       17      Georgetown      MY  2021-12-30 16:21:36   5.4112  100.3354   \n",
       "31       31       Mahebourg      MU  2021-12-30 16:26:20 -20.4081   57.7000   \n",
       "32       32       Mogadishu      SO  2021-12-30 16:26:21   2.0371   45.3438   \n",
       "33       33       Thinadhoo      MV  2021-12-30 16:26:21   0.5333   72.9333   \n",
       "\n",
       "    Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "4      86.02        49          75        1.99  \n",
       "6      75.51        80          88        3.76  \n",
       "9      81.86        81          83        9.44  \n",
       "10     81.32        80          96        6.87  \n",
       "13     77.54        25           0        7.45  \n",
       "15     78.76        79          94       10.16  \n",
       "17     80.89        86          40        5.75  \n",
       "31     78.26        69          40       10.36  \n",
       "32     78.21        74          85       19.89  \n",
       "33     81.36        76          62       12.66  "
      ]
     },
     "execution_count": 10,
     "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": 11,
   "id": "ad718d80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       0\n",
       "City          0\n",
       "Country       3\n",
       "Date          0\n",
       "Lat           0\n",
       "Lng           0\n",
       "Max Temp      0\n",
       "Humidity      0\n",
       "Cloudiness    0\n",
       "Wind Speed    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are any null values in the preferred cities \n",
    "preferred_cities_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d58bb1c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City_ID       158\n",
       "City          158\n",
       "Country       155\n",
       "Date          158\n",
       "Lat           158\n",
       "Lng           158\n",
       "Max Temp      158\n",
       "Humidity      158\n",
       "Cloudiness    158\n",
       "Wind Speed    158\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine if there are any null values in the preferred cities, alternative\n",
    "preferred_cities_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5ce69faa",
   "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>4</th>\n",
       "      <td>Mar Del Plata</td>\n",
       "      <td>AR</td>\n",
       "      <td>86.02</td>\n",
       "      <td>-38.0023</td>\n",
       "      <td>-57.5575</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Cabo San Lucas</td>\n",
       "      <td>MX</td>\n",
       "      <td>75.51</td>\n",
       "      <td>22.8909</td>\n",
       "      <td>-109.9124</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Salinopolis</td>\n",
       "      <td>BR</td>\n",
       "      <td>81.86</td>\n",
       "      <td>-0.6136</td>\n",
       "      <td>-47.3561</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Namatanai</td>\n",
       "      <td>PG</td>\n",
       "      <td>81.32</td>\n",
       "      <td>-3.6667</td>\n",
       "      <td>152.4333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Broken Hill</td>\n",
       "      <td>AU</td>\n",
       "      <td>77.54</td>\n",
       "      <td>-31.9500</td>\n",
       "      <td>141.4333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Puerto Ayora</td>\n",
       "      <td>EC</td>\n",
       "      <td>78.76</td>\n",
       "      <td>-0.7393</td>\n",
       "      <td>-90.3518</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Georgetown</td>\n",
       "      <td>MY</td>\n",
       "      <td>80.89</td>\n",
       "      <td>5.4112</td>\n",
       "      <td>100.3354</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Mahebourg</td>\n",
       "      <td>MU</td>\n",
       "      <td>78.26</td>\n",
       "      <td>-20.4081</td>\n",
       "      <td>57.7000</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Mogadishu</td>\n",
       "      <td>SO</td>\n",
       "      <td>78.21</td>\n",
       "      <td>2.0371</td>\n",
       "      <td>45.3438</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Thinadhoo</td>\n",
       "      <td>MV</td>\n",
       "      <td>81.36</td>\n",
       "      <td>0.5333</td>\n",
       "      <td>72.9333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Country  Max Temp      Lat       Lng Hotel Name\n",
       "4    Mar Del Plata      AR     86.02 -38.0023  -57.5575           \n",
       "6   Cabo San Lucas      MX     75.51  22.8909 -109.9124           \n",
       "9      Salinopolis      BR     81.86  -0.6136  -47.3561           \n",
       "10       Namatanai      PG     81.32  -3.6667  152.4333           \n",
       "13     Broken Hill      AU     77.54 -31.9500  141.4333           \n",
       "15    Puerto Ayora      EC     78.76  -0.7393  -90.3518           \n",
       "17      Georgetown      MY     80.89   5.4112  100.3354           \n",
       "31       Mahebourg      MU     78.26 -20.4081   57.7000           \n",
       "32       Mogadishu      SO     78.21   2.0371   45.3438           \n",
       "33       Thinadhoo      MV     81.36   0.5333   72.9333           "
      ]
     },
     "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": "195b9c8d",
   "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": 19,
   "id": "ddd54f63",
   "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"
     ]
    }
   ],
   "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": 20,
   "id": "62c248c0",
   "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>4</th>\n",
       "      <td>Mar Del Plata</td>\n",
       "      <td>AR</td>\n",
       "      <td>86.02</td>\n",
       "      <td>-38.0023</td>\n",
       "      <td>-57.5575</td>\n",
       "      <td>Gran Hotel Mar del Plata</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Cabo San Lucas</td>\n",
       "      <td>MX</td>\n",
       "      <td>75.51</td>\n",
       "      <td>22.8909</td>\n",
       "      <td>-109.9124</td>\n",
       "      <td>Hotel Tesoro Los Cabos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Salinopolis</td>\n",
       "      <td>BR</td>\n",
       "      <td>81.86</td>\n",
       "      <td>-0.6136</td>\n",
       "      <td>-47.3561</td>\n",
       "      <td>Salinas Park Resort Maçarico AP101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Namatanai</td>\n",
       "      <td>PG</td>\n",
       "      <td>81.32</td>\n",
       "      <td>-3.6667</td>\n",
       "      <td>152.4333</td>\n",
       "      <td>Seagulls Inn Namatani</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Broken Hill</td>\n",
       "      <td>AU</td>\n",
       "      <td>77.54</td>\n",
       "      <td>-31.9500</td>\n",
       "      <td>141.4333</td>\n",
       "      <td>Royal Exchange Hotel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Puerto Ayora</td>\n",
       "      <td>EC</td>\n",
       "      <td>78.76</td>\n",
       "      <td>-0.7393</td>\n",
       "      <td>-90.3518</td>\n",
       "      <td>Finch Bay Galapagos Hotel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Georgetown</td>\n",
       "      <td>MY</td>\n",
       "      <td>80.89</td>\n",
       "      <td>5.4112</td>\n",
       "      <td>100.3354</td>\n",
       "      <td>Cititel Penang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Mahebourg</td>\n",
       "      <td>MU</td>\n",
       "      <td>78.26</td>\n",
       "      <td>-20.4081</td>\n",
       "      <td>57.7000</td>\n",
       "      <td>Shandrani Beachcomber Resort &amp; Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Mogadishu</td>\n",
       "      <td>SO</td>\n",
       "      <td>78.21</td>\n",
       "      <td>2.0371</td>\n",
       "      <td>45.3438</td>\n",
       "      <td>Hotel Juba</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Thinadhoo</td>\n",
       "      <td>MV</td>\n",
       "      <td>81.36</td>\n",
       "      <td>0.5333</td>\n",
       "      <td>72.9333</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Country  Max Temp      Lat       Lng  \\\n",
       "4    Mar Del Plata      AR     86.02 -38.0023  -57.5575   \n",
       "6   Cabo San Lucas      MX     75.51  22.8909 -109.9124   \n",
       "9      Salinopolis      BR     81.86  -0.6136  -47.3561   \n",
       "10       Namatanai      PG     81.32  -3.6667  152.4333   \n",
       "13     Broken Hill      AU     77.54 -31.9500  141.4333   \n",
       "15    Puerto Ayora      EC     78.76  -0.7393  -90.3518   \n",
       "17      Georgetown      MY     80.89   5.4112  100.3354   \n",
       "31       Mahebourg      MU     78.26 -20.4081   57.7000   \n",
       "32       Mogadishu      SO     78.21   2.0371   45.3438   \n",
       "33       Thinadhoo      MV     81.36   0.5333   72.9333   \n",
       "\n",
       "                            Hotel Name  \n",
       "4             Gran Hotel Mar del Plata  \n",
       "6               Hotel Tesoro Los Cabos  \n",
       "9   Salinas Park Resort Maçarico AP101  \n",
       "10               Seagulls Inn Namatani  \n",
       "13                Royal Exchange Hotel  \n",
       "15           Finch Bay Galapagos Hotel  \n",
       "17                      Cititel Penang  \n",
       "31  Shandrani Beachcomber Resort & Spa  \n",
       "32                          Hotel Juba  \n",
       "33                                      "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view the hotel dataframe\n",
    "hotel_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "59e4428a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3300be99fba34a8c87142c0f0e270c4e",
       "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": "6d8ebf1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a3919e89963143f6b415e1151317ffd7",
       "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\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a4478ca8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# add a pop-up marker for each city that displays the hotel name, city name, country, and maximum temperature.\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",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4bf56d8f",
   "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": 26,
   "id": "a0dbd001",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c70240bf7dba4090aa39ad8c9eed1442",
       "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": "9e0bd42e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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