text: import pandas as pd
  
  from src.constants import (
      DATE_READ_SETTINGS,
      DATE_TIME_READ_SETTINGS,
      ELECTRIC_INTERVAL_DATA_CSV_NAME,
      METER_TO_LOCATION_CSV_NAME,
      OCCUPANCY_DATA_CSV_NAME,
      STEAM_DATA_CSV_NAME,
      TENANT_ELECTRIC_INTERVAL_DATA_CSV_NAME,
  )
  
  
  def read_raw_excel_data_to_csv():
      """
      Read in raw Excel data, parse, and save as csvs.
      """
      electric_interval_data = pd.read_excel(
          "data/raw/ConEd_Electric.xlsx", **DATE_TIME_READ_SETTINGS
      )
      electric_interval_data.to_csv(ELECTRIC_INTERVAL_DATA_CSV_NAME)
  
      # Create an ExcelFile from the tenant usage.
      xls = pd.ExcelFile("data/raw/Tenant_Usage.xlsx")
  
      sheet_names = xls.sheet_names
      meter_to_location_lookup = pd.read_excel(xls, sheet_names[0])
      meter_to_location_lookup.to_csv(METER_TO_LOCATION_CSV_NAME, index=False)
  
      # Read in all the individual tenant consumption data.
      tenant_electric_interval_data = pd.concat(
          [
              pd.read_excel(xls, sheet_name, **DATE_TIME_READ_SETTINGS).assign(
                  name=sheet_name
              )
              for sheet_name in sheet_names[1:]
          ]
      )
      tenant_electric_interval_data.to_csv(TENANT_ELECTRIC_INTERVAL_DATA_CSV_NAME)
  
      occupancy_data = pd.read_excel("data/raw/Occupancy.xlsx", **DATE_READ_SETTINGS)
      occupancy_data.to_csv(OCCUPANCY_DATA_CSV_NAME)
  
      steam_data = pd.read_excel("data/raw/ConEd_Steam.xlsx", **DATE_TIME_READ_SETTINGS)
      steam_data.to_csv(STEAM_DATA_CSV_NAME)
  