This project includes cleaning up a large timeseries data set using timestamps and Pandas, then adding to holiday and temperature data. Then it takes a look at how we consume electricity using Seaborn with regards to holidays and temperature. It also provides a SARIMA model that can be used to predict future electrical consumption.
If you would like to run my code in a python environment, connected to Kaggle data sets, I have my kaggle profile as linked.
This PowerBI dashboard is currently in PPT form to share. It is creates an interactive workspace for users to see how PJM's electrical data can be broken down over days, holidays, and temperatures.