This is a bunch of (not well organized) code to analyze engine data generated by a Garmin G1000 NXi panel installed on a Cirrus SR20 G6 aircraft, with a Lycoming IO-390 4-cylinder engine.
The idea is to analyze engine parameters over a long time, like months or years, to detect developing patterns.
Browse around, clone, change, submit PRs, do whatever you want with this code while respecting the license (GPL v3). Just don't expect any warranty from my side. This is purely personal interest as an aircraft owner and pilot.
The code was written in Python 3.7 using Pandas, NumPi, SciPy and Matplotlib.
Dependencies:
pip3.7 install pandas numpy scipy pyarrow jupyterlab matplotlib
I recommend using virtualenv if you don't want to mess with your Python default installation.
Performance note:
Loading 500 hours of data consumes about 1-1.5 GB of RAM, once the data is loaded. Parsing all that from CSV files may take half an hour on a modern computer. Save your data to a feather file after parsing the CSV files, to avoid the CSV parsing pain.