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Recommending hotels and travel destinations to travelers based on weather preferences using Pandas Dataframe, Matplotlib, CitiPy, SciPy, Python Requests, APIs, JSON Traversals, Jupyter Notebook 6.3.0

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ramya-ramamur/World_Weather_Analysis

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World_Weather_Analysis

Overview

An analysis and visualization of weather data across 500+ cities worldwide for a travel app called "PlanMyTrip" that will use the data to recommend ideal hotels based on clients' weather preferences to travellers so that they can plan their itinerary.

Resources

  • Data Source:
    1. Weather Database: WeatherPy_Database.csv
    2. Vacation Data : WeatherPy_vacation.csv
  • Software: Python 3.8.8, Pandas Dataframe, Matplotlib, CitiPy, SciPy, Python Requests, APIs, JSON Traversals, Jupyter Notebook 6.3.0
  • API's accessed: OpenWeatherMap API, Google Maps and Places API, Google Maps Directions API

Summary of Results

Deliverable 1: Retrieve Weather Data

Generated a set of 2,000 random latitudes and longitudes, and retrieved the nearest cities. Performed an API call with the OpenWeatherMap and the following information was extracted from the API call:

  • Latitude and longitude
  • Maximum temperature
  • Percent humidity
  • Percent cloudiness
  • Wind speed
  • Weather description (for example, clouds, fog, light rain, clear sky) The above data was captured in a Pandas Dataframe and exported to a "WeatherPy_Database.csv" file. An excerpt of the dataframe is as follows.

weather_database

Deliverable 2: Create a Customer Travel Destinations Map

Using input statements from customer to get customer weather preferences, then used those preferences and data collected in "WeatherPy_Database.csv" file, to identify potential travel destinations and nearby hotels, and exported the data to a 'WeatherPy_vacation.csv" file. The data is visualized on a world map that show those destinations on a marker layer map with pop-up markers.

vacation_search

WeatherPy_vacation_map

Deliverable 3: Create a Travel Itinerary Map

Using the Google Directions API and data from 'WeatherPy_vacation.csv", created a sample travel itinerary that shows the route between four cities chosen from the customer’s possible travel destinations. Then, created a marker layer map with a pop-up marker for each city on the itinerary.

Sample Travel Itinerary of four cities in USA starting and ending at North Myrtle Beach.

Sample Travel Itinerary

Vacation Travel Route

WeatherPy_travel_map

Vacation Hotel and Weather Pop-up Marker Map

WeatherPy_travel_map_markers 6 53 19 PM

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Recommending hotels and travel destinations to travelers based on weather preferences using Pandas Dataframe, Matplotlib, CitiPy, SciPy, Python Requests, APIs, JSON Traversals, Jupyter Notebook 6.3.0

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