- pandas module in Python
- SQLAlchemy module in Python
- Flask
I am taking a trip to Hawaii and have decided to do some analysis based off of some climate data found in a SQLite database. The following analyses were done:
- Using SQLAlchemy to reflect existing databases to classes in Python
- Using queries to retrieve the last 12 months of precipitation data and plotting them over time using a pandas DataFrame
- Designing queries to obtain the total number of stations, the most active stations, and the last 12 months of temperature observation data (summarized as a histogram)
- Creating a Flask API app to create routes that retrieve JSON data such as precipitation values by date, stations, temperature observations from the last year, and min, max, and average temperatures within a specified date range.
Extra analyses were also done to:
- Test if June and December temperature observations were significantly different using a t-test
- Plotting the average temperature and the min/max range as a bar chart for my chosen trip date (4/10/2014-4/22/2014) based off of the previous year's corresponding date
- Daily rainfall average based off of historical data for my chosen date range
An additional side analysis was also done to justify why a line plot may not always be the best choice for dealing with certain datasets.