02 — Feature Engineering
Transforms raw demand and weather data into ML-ready features including humidex, cooling degree hours, demand momentum, and peak context variables.
feature-engineering humidex cooling-degree-hours temporal-features
Pythonpandasnumpymatplotlibseaborn
Key Findings
- ● Humidex and daily CDH emerge as stronger predictors than raw temperature alone
- ● Previous day's max demand captures system-level momentum that weather features miss
- ● Peak context features (current threshold, peaks so far) provide essential operational framing