In this assignment, we explore regional climate data in preparation for our respective trip to Honolulu, Hawaii. We conduct analysis of our findings – all to assist in the planning of fun excursions, and of course the packing of cute beach weather attire😉.

We utilize SQL Alchemy ORM queries, Pandas and Matplotlib. With SQL Alchemy, we are able to connect to a SQLite database. From there we completed summary statistics, produced some helpful charts (including a histogram!!!!), and provided for some overall additional climate analysis.

In part 2, we switched roles – from a thirsty information recipient, to an all-powerful information provider :o. Specifically, we used the Flask (jsonify) function to convert our API data to a legit JSON response object. Converting query results from our previous precipitation analysis to a data dictionary was no easy feat. In the end, creating a simple browser portal/search list from which to retrieve data customized to our preferences (especially with respect to user input dates and the min, max and average temperatures associated with those dates), was rewarding.