Create 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 and the OpenWeatherMap API to create a representative model of weather across world cities.
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
After each plot add a sentence or too explaining what the code is and analyzing.
Run linear regression on each relationship, only this time separating them into Northern Hemisphere (greater than or equal to 0 degrees latitude) and Southern Hemisphere (less than 0 degrees latitude):
Northern Hemisphere - Temperature (F) vs. Latitude Southern Hemisphere - Temperature (F) vs. Latitude Northern Hemisphere - Humidity (%) vs. Latitude Southern Hemisphere - Humidity (%) vs. Latitude Northern Hemisphere - Cloudiness (%) vs. Latitude Southern Hemisphere - Cloudiness (%) vs. Latitude Northern Hemisphere - Wind Speed (mph) vs. Latitude Southern Hemisphere - Wind Speed (mph) vs. Latitude
Explain what the linear regression is modelling such as any relationships you notice and any other analysis you may have.
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 a CSV of all retrieved data and a PNG image for each scatter plot.
Use jupyter-gmaps and the Google Places API for this part of the assignment.
Create a heat map that displays the humidity for every city from the part I
Narrow down the DataFrame to find your ideal weather condition. For example:
A max temperature lower than 80 degrees but higher than 70, Wind speed less than 10 mph, Zero cloudiness.
Drop any rows that don’t contain all three conditions. You want to be sure the weather is ideal.
Use Google Places API to find the first hotel for each city located within 5000 meters of your coordinates.
Plot the hotels on top of the humidity heatmap with each pin containing the Hotel Name, City, and Country.