Upon exploring the dataset and choosing a start and end date for the a trip
The date range is approximately 3-15 days total
Used the Jupyter Notebook to perform the following:
- Used SQLAlchemy's `create_engine` to connect to the dataset
- Used SQLAlchemy's `automap_base()` to reflect tables into classes and saved a reference to those classes called `Station` and `Measurement`
- Designed a Query to retrieve the last 12 months of precipitation data
- Load Query results into Pandas DataFrame and set index to date column
- Sort DataFrame values by Date
- Print the summary statistics and plot the precipitation data
- Queried to calculate the total number of stations and the most active station
- Plot the temperature frequency at the most active station
After completed initial analysis, a Flask API was designed based on the above queries.