Congratulations! You've decided to treat yourself to a long holiday vacation in Honolulu, Hawaii. To help with your trip planning, you decide to do a climate analysis about the area. The following sections outline the steps that you need to take to accomplish this task.
In this section, you’ll use Python and SQLAlchemy to do a basic climate analysis and data exploration of your climate database. Specifically, you’ll use SQLAlchemy ORM queries, Pandas, and Matplotlib.
Now that you’ve completed your initial analysis, you’ll design a Flask API based on the queries that you just developed.
Module10_Challenge.docx == the FULL and detailed instruction set for this entire challenge.
Under the "SurfsUp" folder:
1_climate_Helotie.ipynb == the Jupyter notebook for Part 1.
2_app_Helotie.py == the Python script that spawns a local Flask session in a web browser for Part 2.
The "Resources" folder contains the CSV files and the SQLLite file which gets imported.