Climate and Precipitation Analysis

Summary

This project is designed to explore and analyze data of climate database by using SQLAlchemy ORM queries, and Pandas and Matplotlib in Python. A Flask API is created to store all the information.

Data Source

hawaii.sqlite

Tool

Python: SQLAlchemy, Pandas and Matplotlib

Visualization

Precipitation Analysis

Station Analysis of temperature observation data for the last 12 months

Flask Routes

• /

  • Home page.

  • List all routes that are available.

• /api/v1.0/precipitation

  • Convert the query results to a Dictionary using date as the key and prcp as the value.

  • Return the JSON representation of your dictionary.

• /api/v1.0/stations

  • Return a JSON list of stations from the dataset.

• /api/v1.0/tobs

  • query for the dates and temperature observations from a year from the last data point.
  • Return a JSON list of Temperature Observations (tobs) for the previous year.

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

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

  • When given the start only, calculate TMIN, TAVG, and TMAX for all dates greater than and equal to the start date.

  • When given the start and the end date, calculate the TMIN, TAVG, and TMAX for dates between the start and end date inclusive.