examining results on colchester

This commit is contained in:
Khalim Conn-Kowlessar 2025-02-25 08:19:08 +00:00
parent c3049732f0
commit 0ffc59861c

View file

@ -233,7 +233,8 @@ class AssetList:
"secondheat-description": "epc_secondary_heating",
"transaction-type": "epc_reason",
"energy-consumption-current": "epc_heat_demand",
"photo-supply": "epc_photo_supply"
"photo-supply": "epc_photo_supply",
"estimated": "estimated"
}
FIND_EPC_DATA_NAMES = {
"heating_text": "epc_estiamted_heating_kwh",
@ -714,6 +715,22 @@ class AssetList:
columns=self.rename_map
)
# We fill any standard columns that are not in the data because they were not provided by the landlord
missing_variables = [
v for v in [
self.STANDARD_EXISTING_PV,
self.STANDARD_HEATING_SYSTEM,
self.STANDARD_UPRN,
self.STANDARD_PROPERTY_TYPE,
self.STANDARD_YEAR_BUILT,
self.STANDARD_WALL_CONSTRUCTION,
self.STANDARD_HEATING_SYSTEM,
self.STANDARD_EXISTING_PV
] if v not in self.standardised_asset_list.columns
]
for v in missing_variables:
self.standardised_asset_list[v] = None
def merge_data(self, df: pd.DataFrame):
"""
Used to insert data into the standardised asset list, based on the domna property id
@ -963,7 +980,6 @@ class AssetList:
# Extraction
######################################################
# TODO When filterting like this, 627 properties are flagged as not needing a CIGA check and 582 are flagged
# as needing a CIGA check. What is the logic we should be applying here?
self.standardised_asset_list["non_intrusive_indicates_cavity_extraction"] = (
(self.standardised_asset_list["non-intrusives: Construction"] == "CAVITY") &
@ -974,6 +990,15 @@ class AssetList:
)
)
z = self.standardised_asset_list[
self.standardised_asset_list["non-intrusives: CIGA Check Required"] == "YES"
]
z["non-intrusives: Insulated"].value_counts()
z["non-intrusives: Material"].value_counts()
z[self.ATTRIBUTE_SAP_THRESHOLD_AND_BELOW].value_counts()
z[self.EPC_API_DATA_NAMES["current-energy-efficiency"]].max()
zz = z[z[self.EPC_API_DATA_NAMES["current-energy-efficiency"]] == 105]
######################################################
# Solar
######################################################