This open source Python program, overall, reads data using the Torque API, handles missing values and outliers, calculates statistics, normalizes scores using two techniques - Min-Max normalization and Z-score normalization, performs data pivoting, calculates overall scores, ranks applications, and saves the results back up to Torque.

See DESIGN.md for more information.

Usage

Copy config.py.tmpl to config.py and update the variables

$ cp config.py.tmpl config.py
$ $EDITOR config.py

Install dependencies

$ pip install pandas numpy seaborn matplotlib torqueclient

Run

$ python main.py [--csv]

The --csv option is to output the result to a csv file rather than uploading to torque.

Install as a local library

$ pip3 install -e .