Developed a live API using Python and SqLite data file.

• SqLite file contains Weather Station data.
  • 'Measurement' class : Station name, date, precipitation (prcp), and temperature (tobs).
  • 'Station' class : Station number, Station name, latitude, longitude, and elevation.

Working with the data

• Load SqLite file into Python Notebook and identify classes and reflect into SqlAlchemy.
• Assign 'measurement' and 'station" to variable called 'Measurement' and 'Station'
• Create a Session, from the 'Measurement' class query columns listed above. From the 'Station' class, query columns listed above as well.
• Analyze the data. How many stations are there? What is the most active station?

Visualizing the data : Python Notebook Link

• Design a query to retrieve the last 12 months of prcp data and graph.

* Design queries to get an idea of the temperature distribution and trends. Generate a box and whisker to visualize the upper and lower bounds. Generate a histogram to visualize the temperature distribution.

Develop a live API using Flask : Flask App Notebook Link

• Develop a live API using Flask that will display given data from SqLite file.
• Three available API's:

• To run Flask app, all dependencies must be installed locally (using pip for example), and python app run from the terminal.