This repository contains the Python codes to find the weather data for at least 500 unique cities, to determine whether there are similarities for cities as they get closer to the equator. These cities are generated randomly. The data is then visually presented on a scatter plot.
Analysis:
- Temperature vs. Latitude: There is a strong correlation of temperatures and the city's latitude. As it gets closer to the equator, it seems like generally the temperature rises accordingly.
- Humidity % vs. Latitude: Doesn't seem like there is a correlation.
- Cloudiness(%) vs. Latitude: No correlation.
- Wind Speed (mph) vs. Latitude: No correlation.
NOTE: The current weather data is based on one specific day. To have a better representation, we probably need to pull data from a range of dates / months / years.
API calls
Openweathermapy.core
Pandas
Numpy
Random
OS
Time
Requests
CityPy
Matplotlib
Seaborn
Scatter Plots
Dataframe