hawaii

Description

Query weather observatory database via SQLAlchemy in Python. Using the query results, we analyze weather data over for a time period in the past.

A Flask app is also provided to query the database.

Methods

1. SQLALchemy is used to query the SQLite database of observations.
2. Plots are constructed with matplotlib.
3. A Flask app is provided to query the database. We utilize the fuzzy date parsing option of the dateutil.parser.parse function. This allows us to avoid checking input dates for valid entries.

Results

• The Jupyter notebook hawaii.ipynb contains the results of querying the database. View the notebook via nbviewer
• The Jupyter notebook dateparsing.ipynb gives examples of using the dateutil.parser.parse function to produce ISO 8601 dates YYYY-MM-DD. View the notebook via nbviewer.
• stations.ipynb explores the range of available dates in the database for the various stations and the effect of querying for dates with different formats (datetime objects versus dates as strings). View the notebook via nbviewer
• app.py is the code for the Flask app to query the database. We have incorporated the dateutil.parser.parse function to allow for flexible entry of dates. Queries using dates outside the range of the datebase do not produce errors at this time. If a queried date falls outside of the datebase range, the query returns null if appropriate.