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World Weather Analysis

BootCamp Challenge Week6 Using API´s to visualize Data

Overview

For this week, we will help the travel company Planmytrip which offer its clients a variety of travel options depending on the weather they prefer. For this we will use the Google maps platform, API requests and Jupyter maps.

Results

We started by generating a file with random coordinates, from this we filtered the places with temperatures below a maximun deteminated, and the results were saved in a database Weatherpy_Database.csv. From there, according to the client's weather preference, we stored the results in WeatherPy_vacation.csv file, and we showed them a Google map with the places that fitted their selection with a suggest hotel.

WeatherPy_vacation_map.png WeatherPy_vacation_map

Subsequently, the client is asked to refine the search based in its weather preference, and then, assuming that the client has chosen 4 places to visit (in this case, we chose the North of Spain), and we presented a Google map with a proposed route to visit the places and another map with a hotel suggestion.

North of Spain travel route (WeatherPy_travel_map.png) WeatherPy_travel_map

North of Spain travel hotels (WeatherPy_travel_markers) WeatherPy_travel_markers

Summary

For me, this project seemed very illustrative about the management of APIs to get information that already exists and it can be consulted. In this project we consulted Google Maps combining the knowledge acquired from Python, Pandas, Mathplotlib. A very good resume for this knowledge.