In this example, you'll be creating a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. To accomplish this, you'll be utilizing a simple Python library, the OpenWeatherMap API, and a little common sense to create a representative model of weather across world cities.
Your objective is to build 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

Your final notebook must:

Randomly select at least 500 unique (non-repeat) cities based on latitude and longitude.
Perform a weather check on each of the cities using a series of successive API calls.
Include a print log of each city as it's being processed with the city number and city name.
Save both a CSV of all data retrieved and png images for each scatter plot.

As final considerations:

Create a new GitHub repository for this project called API-Challenge (note the kebab-case). Do not add to an existing repo

You must complete your analysis using a Jupyter notebook.
You must use the Matplotlib or Pandas plotting libraries.
You must include a written description of three observable trends based on the data.
You must use proper labeling of your plots, including aspects like: Plot Titles (with date of analysis) and Axes Labels.
See Example Solution for a reference on expected format.