Climate analysis and data exploration - University of Birmingham Assignment

I have used Python, SQLAlchemy’s create_engine & ORM queries, Pandas, and Matplotlib to perform climate analysis and data exploration of a provided climate database (hawaii.sqlite).

what is included in the analysis of precipitation in the area:

• The most recent date in the dataset.

• Using this date, I have retrieved the previous 12 months of precipitation data by querying the 12 previous months of data.

• Select only the date and prcp values.

• Load the query results into a Pandas DataFrame, and set the index to the date column.

• Sort the DataFrame values by date.

• Plots with the results

To perform an analysis of stations in the area, I have designed:

• A query to calculate the total number of stations in the dataset.

• A query to find the most active stations (the stations with the most rows)

• I have used functions such as func.min, func.max, func.avg, and func.count.

• A query to retrieve the previous 12 months of temperature observation data (TOBS).

I have designed a Flask API based on the queries that I have developed.

Flask routes:

• / Homepage. List all available routes.

• /api/v1.0/precipitation

• /api/v1.0/stations

• /api/v1.0/tobs Query the dates and temperature observations of the most active station for the previous year of data.

• /api/v1.0/start and /api/v1.0/start/end Return a JSON list of the minimum temperature, the average temperature, and the maximum temperature for a given start or start-end range.