The main purpose of this project is to help travelers to plan ideal trip anywhere in the world based on weather.
In this project, we learned how to apply analytical, statistical , and visualization skills to get the data from websites to an API. For very large amount of data, it's a very effective way to gather the data. One of the most popular format of the retrieved data is JSON. With the help of Python's CityPy module , jupyter notebook, Pandas, APIs, JSON, we have collected weather data from approximately 700 cities all around the world. Then with the help of matplotlib library and google maps, places, and direction APIs, we were able to help a traveler to plan a trip anywhere in the world.
While doing this project, we were able to show the relationship between latitude and different weather parameters by doing statistical analysis on the retrieved data. Visualization of the data for traveler's requirement helped to plan the trip more effectively.
All the results in this project are optimised for traveler input temperatures between 75 degrees farenheit to 90 degrees farenheit.
So when the app user enters the temerature between 75 to 90 degrees, we have collected all the weather related data from the openweather API and then after doing analysis on it, helped the user to chosse the destinations with the help of google maps APIs. Then the traveler was able to create an itenarary for the desired trip.