Summary

This project utilizes Python, API’s, and JSON to try and answer a fundamental question: “What’s the weather like as we get closer to the equator?” Click here to see the Weather Project.

I randomly assigned 1,500 Latitude and Longitudes, then used the Python CitiPy library to find the city closest to the Lat/Lon (dropping all duplicates) to get a listing of 606 cities. I utilized OpenWeatherMapAPI to get the weather for the cities (dropping cities with no data) to create a dataframe of weather information for over 500 cities.

The data is saved to CSV and the data is analyzed to showcase the relationship between latitude and temperature/humidity/cloudiness/wind speed. I then used MatplotLib scatter plots to view:

• Latitude vs. Temperature (F)
• Latitude vs. Humidity (%)
• Latitude vs. Cloudiness (%)
• Latitude vs. Wind Speed (mph)