There are four main objectives to this homework:
Raw data will be cleaned and beaten into submission using Pandas and Jupyter Notebook. The .csv files will be inspected for NaNs, missing values, duplicates, and other such gaps.
SQL Alchemy is utilized to model table schemas and create a sqlite database for the cleaned data. Jupyter Notebook will again be used for this engineering.
After being readied for exploration and analysis, several analyses will be performed using a combination of SQLAlchemy ORM queries, Pandas, and Matplotlib. The analyses include:
- Precipitation Analysis
- Station Analysis
- Temperature Analysis
Using the queries developed in the above activity, a Flask API has been designed to return user queries in a json format. Temperature (min, max, and average) and date observations as well as stations are included in the routes.