For Module 6, we traveled :). We traversed all over the globe through JSON data structures, discovering all kinds of cool meteorological relationships. These relationships were analyzed for their correlation strength, or lack thereof. Pearson’s r values and Linear Regression Equations were determined, and fun data plots dotted the landscape of groovy red regression lines. As a programming finale, our JSON traversals lead to the investigation of desirable vacation destinations (after bootcamp ends... and good job pays!!!). Colorful geoViews dazzled, and hover messages delighted :). I enjoyed the exercise immensely, and am now daydreaming of post-bootcamp adventures :).

WeatherVacationPy File Contents (7 files total):

Jupyter Notebook Python programs (2) -- WeatherPy.ipynb, VacationPy.ipynb

Portable Network Graphics – PNG output (4) -- City_Max_Latitude_vs_Temperature.png, City_Max_Latitude_vs_Humidity.png, City_Max_Latitude_vs_Cloudiness.png, City_Max_Latitude_vs_WindSpeed.png

API Keys (1): api_keys.py