def natural_gas_consumption_location_heating_region_geometry_foundation_type(
self, screen_scen):
df = util.create_dataframe(self.session, rdb, screen_scen=screen_scen)
df = util.assign_climate_zones(df)
df = util.assign_heating_location(df)
df = util.assign_vintage(df)
df = util.assign_foundation_type(df)
df = util.assign_natural_gas_consumption(df)
df = df.groupby([
'Dependency=Location Heating Region',
'Dependency=Geometry Foundation Type'
])
count = df.agg(['count']).ix[:, 0]
weight = df.agg(['sum'])['Weight']
df = df[['thm_nrm']].sum()
df['Count'] = count
df['Weight'] = weight
df['thm_nrm_per_home'] = df['thm_nrm'] / df['Count']
df['thm_nrm_total'] = df['thm_nrm_per_home'] * df['Weight']
df = df.reset_index()
df = df.sort_values(by=[
'Dependency=Location Heating Region',
'Dependency=Geometry Foundation Type'
]).set_index([
'Dependency=Location Heating Region',
'Dependency=Geometry Foundation Type'
])
return df
def natural_gas_consumption_location_heating_region_vintage(
self, screen_scen):
df = util.create_dataframe(self.session, rdb, screen_scen=screen_scen)
df = util.assign_climate_zones(df)
df = util.assign_heating_location(df)
df = util.assign_vintage(df)
df = util.assign_natural_gas_consumption(df)
df = df.groupby(
['Dependency=Location Heating Region', 'Dependency=Vintage'])
count = df.agg(['count']).ix[:, 0]
weight = df.agg(['sum'])['Weight']
df = df[['thm_nrm']].sum()
df['Count'] = count
df['Weight'] = weight
df['thm_nrm_per_home'] = df['thm_nrm'] / df['Count']
df['thm_nrm_total'] = df['thm_nrm_per_home'] * df['Weight']
df = df.reset_index()
df['Dependency=Vintage'] = pd.Categorical(
df['Dependency=Vintage'],
['<1950', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s'])
df = df.sort_values(
by=['Dependency=Location Heating Region', 'Dependency=Vintage'
]).set_index([
'Dependency=Location Heating Region', 'Dependency=Vintage'
])
return df
def vintage(self):
df = util.assign_vintage(self.session)
df = add_option_prefix(df)
df = df[[
'Option=<1950', 'Option=1950s', 'Option=1960s', 'Option=1970s',
'Option=1980s', 'Option=1990s', 'Option=2000s', 'Count', 'Weight'
]]
return df
def natural_gas_consumption_vintage(self, screen_scen):
df = util.create_dataframe(self.session, rdb, screen_scen=screen_scen)
df = util.assign_vintage(df)
df = util.assign_natural_gas_consumption(df)
df = df.groupby(['Dependency=Vintage'])
count = df.agg(['count']).ix[:, 0]
weight = df.agg(['sum'])['Weight']
df = df[['thm_nrm']].sum()
df['Count'] = count
df['Weight'] = weight
df['thm_nrm_per_home'] = df['thm_nrm'] / df['Count']
df['thm_nrm_total'] = df['thm_nrm_per_home'] * df['Weight']
df = df.reset_index()
df['Dependency=Vintage'] = pd.Categorical(df['Dependency=Vintage'], ['<1950', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s'])
df = df.sort_values(by=['Dependency=Vintage']).set_index(['Dependency=Vintage'])
return df
def natural_gas_consumption_geometry_foundation_type(self, screen_scen):
df = util.create_dataframe(self.session, rdb, screen_scen=screen_scen)
df = util.assign_climate_zones(df)
df = util.assign_heating_location(df)
df = util.assign_vintage(df)
df = util.assign_foundation_type(df)
df = util.assign_natural_gas_consumption(df)
df = df.groupby(['Dependency=Geometry Foundation Type'])
count = df.agg(['count']).ix[:, 0]
weight = df.agg(['sum'])['Weight']
df = df[['thm_nrm']].sum()
df['Count'] = count
df['Weight'] = weight
df['thm_nrm_per_home'] = df['thm_nrm'] / df['Count']
df['thm_nrm_total'] = df['thm_nrm_per_home'] * df['Weight']
df = df.reset_index()
df = df.sort_values(by=['Dependency=Geometry Foundation Type']).set_index(['Dependency=Geometry Foundation Type'])
return df
def electricity_consumption_location_heating_region_vintage(self, screen_scen):
df = util.create_dataframe(self.session, rdb, screen_scen=screen_scen)
df = util.assign_climate_zones(df)
df = util.assign_heating_location(df)
df = util.assign_vintage(df)
df = util.assign_electricity_consumption(df)
df = df.groupby(['Dependency=Location Heating Region', 'Dependency=Vintage'])
count = df.agg(['count']).ix[:, 0]
weight = df.agg(['sum'])['Weight']
df = df[['kwh_nrm']].sum()
df['Count'] = count
df['Weight'] = weight
df['kwh_nrm_per_home'] = df['kwh_nrm'] / df['Count']
df['kwh_nrm_total'] = df['kwh_nrm_per_home'] * df['Weight']
df = df.reset_index()
df['Dependency=Vintage'] = pd.Categorical(df['Dependency=Vintage'], ['<1950', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s'])
df = df.sort_values(by=['Dependency=Location Heating Region', 'Dependency=Vintage']).set_index(['Dependency=Location Heating Region', 'Dependency=Vintage'])
return df
def electricity_consumption_vintage(self, screen_scen):
df = util.create_dataframe(self.session, rdb, screen_scen=screen_scen)
df = util.assign_vintage(df)
df = util.assign_electricity_consumption(df)
df = df.groupby(['Dependency=Vintage'])
count = df.agg(['count']).ix[:, 0]
weight = df.agg(['sum'])['Weight']
df = df[['kwh_nrm']].sum()
df['Count'] = count
df['Weight'] = weight
df['kwh_nrm_per_home'] = df['kwh_nrm'] / df['Count']
df['kwh_nrm_total'] = df['kwh_nrm_per_home'] * df['Weight']
df = df.reset_index()
df['Dependency=Vintage'] = pd.Categorical(
df['Dependency=Vintage'],
['<1950', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s'])
df = df.sort_values(by=['Dependency=Vintage']).set_index(
['Dependency=Vintage'])
return df