This project has 2 parts: WeatherPy and VacationPy.
In this part python script is created to visualize the weather over 500 cities with varying distance from equador. Here I used citipy Python library and OpenWeatherMap API.
-
By using OpenWeatherMap API I retrieve weather data from cities list generated in starter code. The goal is to create plots to showcase the relationship between weather variables (temperature, humidity, cloudiness, wind speed) and latitude. Outputs of those findings can be found in output_data.
-
Goal is to computee the linear regression for each relationship listed in first requirement for Northern Hemisphere and Southern Hemisphere. Also detailed analysis was done after each pair of plots, explaining what linear regression is modeling. Analysus can be found in Jupyter Notebook and all outputs are saved in output_data.
In this part of project goal it to plan future vacation by using weather data skills. Here I used geoViews Python library and Geoapify API. Following map visualisations are created:
-
Map that displays a point for every city in the city_data_df DataFrame. The size of the point should be the humidity in each city. This Map can be found in output_data.
-
Map that displays ideal weather conditions {(max.tem <27 & >21), wind speed <4.5, cloudiness zero} and for each city(that displays those ideal weather conditions) by using Geoapify API located hotel in radius of 10,000m. This Map can be found in output_data.
Very interesting project this was to work on. I greatly appreciate help from Learning Assistent.