WeatherPy is a tool that creates scatterplots of weather metrics based on geolocation data for over 500 randomly selected cities from all over the world. It helps us visualise relationships between the location of a city relative to the equator and some weather metrics such as temperature, cloudiness, humidity, and wind speed.
WeatherPy selects at least 500 cities from 2,000 randomly generated coordinates using CityPy and determines their locations based on Google Maps. The weather for each city is extracted from OpenWeatherMap. The graphs were then created using Matplotlib.
Let's explore the weather trends for 629 cities on October 14th, 2018.
Based on the map, many cities selected follow the coastlines; inner parts of of Africa, of Australia, and of South America had sparsely dotted regions (i.e., not a lot of cities were selected from these areas). The sparse region in Australia is most likely the desert Outback. In South America, the empty regions could include the Patagonian Steppe (Argentina), La Guajira desert (Colombia), and the Amazon rainforest. More cities were selected south of the equator in Africa; the northern part of the continent has fewer cities because it is dominated by the Sahara desert. It was notable that cities from small island nations in the Pacific and the Atlantic were included in the random selection.
