text_plain_output_1.png image_output_1.png
import pandas as pd

elec_all_data = pd.read_csv('../input/buildingdatagenomeproject2/electricity_cleaned.csv', index_col='timestamp', parse_dates=True)

buildingname = 'Panther_office_Hannah'
office_example = pd.DataFrame(elec_all_data[buildingname].truncate(before='2017-01-01'))

meta = pd.read_csv('../input/buildingdatagenomeproject2/metadata.csv', index_col='building_id')

meta.loc[buildingname]

meta.loc[buildingname]['sqm']

office_example_normalized = office_example / meta.loc[buildingname]['sqm']

meta[meta.site_id == 'Wolf'].head()