WeatherPy

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

The script "WeatherPy"

• 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).

Results

Processing Cities

Temperature (F) vs. Latitude

Humidity (%) vs. Latitude

Cloudiness (%) vs. Latitude

Wind Speed (mph) vs. Latitude