Data scraper process:
- Documents necessary energy conversions (summary CSV does this...but not using the summary using the output CSV that has all the reporting data).
- Holds variables for gas and elec pricing.
- Holds variables for source-site factors.
- Holds variables for CO2e factors.
- Combines all EnergyPlus default CSV files in defined directory.
- Grabs the wanted columns from the merged dataframe. Renamed columns. Cleaned data if necessary.
- Gets the annual energy data
- Uses the pricing variable to convert to costs.
- Combines the annual data and costs into grouped dataframe.
- Exports annual data to CSV. *Determines the delta from base case (existing) conditions.
- Establish dataframes for each condition.
- Merges these dfs.
- Performs delta calculations and adds columns to df.
- Exports grouped df to CSV.
- Repeats this for peak demand, but first found the day/hour of the peak performer.
