Three models were developed to predict monthly energy cost using building characteristics, occupancy, customer type, and regional information. A multiple linear regression (MLR), a Random Forest (RF) model, and an Extreme Gradient Boosting (XGBoost) model. Model performance was evaluated using the Root Mean Square Error (RMSE) and the Coefficient of Determination (R²)

This R script details the process of using API call from "nasapower" package, to download temperature data for statistical analysis to isolate heatwaves frequency and visualizations of trends.