A Python script to visualize data points of the weather for 500+ cities across the world of varying distance from the equator. For this project, I utilized Python requests, the OpenWeatherMap API, and JSON traversals to create a series of scatter plots to showcase the following relationships:
- Temperature (F) vs. Latitude
- Humidity (%) vs. Latitude
- Cloudiness (%) vs. Latitude
- Wind Speed (mph) vs. Latitude
- Randomly selects at least 500 unique (non-repeat) cities based on latitude and longitude.
- Performs a weather check on each of the cities using a series of successive API calls.
- Prints a log of each city as it's being processed with the city number and city name.
- Saves both a CSV of all data retrieved and png images for each scatter plot.
This project was for an assignment at Washington University's Data Analytics Boot Camp (2019).
