Data Science SQL Alchemy Activity: Surfs Up!

Step 1 - Climate Analysis and Exploration

Used Python and SQLAlchemy to do basic climate analysis and data exploration of the Hawaii climate database. All of the Precipitation, Temperature and Station analysis was completed using SQLAlchemy ORM queries, Pandas, and Matplotlib.

Step 2 - Climate App

Designed a Flask API based on the queries that were developed as part of Step 1. Used Flask jsonify to convert the API data into valid JSON response objects.

Flask Routes

• /

  • Home page that lists all routes that are available.

• /api/v1.0/precipitation

  • Returns the JSON representation of the precipitation data dictionary object.

• /api/v1.0/stations

  • Returns a JSON list of stations from the dataset.

• /api/v1.0/tobs

  • Returns a JSON list of Temperature Observations (tobs) for the previous year.

• /api/v1.0/<start> and /api/v1.0/<start>/<end>

  • Returns a JSON list of the minimum temperature, the average temperature, and the max temperature for a given start or start-end range.