mirror of
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199 lines
6.8 KiB
Python
199 lines
6.8 KiB
Python
"""
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This script is to calculate the ABS for the Places for People London project
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"""
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import os
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import pandas as pd
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# London
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pfp_london_cav = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_areas_surrounding_london_reviewed_standardised_15052025.xlsx",
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sheet_name="Cav Route",
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header=1
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)
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pfp_london_cav = pfp_london_cav.rename(columns={"Route": "Route March"})
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pfp_london_pv = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_areas_surrounding_london_reviewed_standardised_15052025.xlsx",
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sheet_name="PV Route",
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header=1
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)
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pfp_london_pv = pfp_london_pv.rename(columns={"Route": "Route March"})
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pfp_london_cav["location"] = "London"
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pfp_london_pv["location"] = "London"
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# East
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pfp_east_cav = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_east_reviewed_standarised_15052025.xlsx",
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sheet_name="Cav Route",
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header=1
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)
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pfp_east_cav = pfp_east_cav.rename(columns={"Route": "Route March"})
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pfp_east_pv = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_east_reviewed_standarised_15052025.xlsx",
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sheet_name="PV Route",
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header=1
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)
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pfp_east_pv = pfp_east_pv.rename(columns={"Route": "Route March"})
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pfp_east_cav["location"] = "East"
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pfp_east_pv["location"] = "East"
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# North east
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pfp_north_east_cav = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_north_east_reviewed_standardised_15052025.xlsx",
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sheet_name="Cav Route",
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header=1
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)
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pfp_north_east_cav = pfp_north_east_cav.rename(columns={"Route": "Route March"})
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pfp_north_east_pv = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_north_east_reviewed_standardised_15052025.xlsx",
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sheet_name="PV Route",
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header=1
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)
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pfp_north_east_pv = pfp_north_east_pv.rename(columns={"Route": "Route March"})
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pfp_north_east_cav["location"] = "North East"
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pfp_north_east_pv["location"] = "North East"
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# North West
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pfp_north_west_cav = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_north_west_reviewed_standardised_15052025.xlsx",
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sheet_name="Cav Route",
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header=1
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)
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pfp_north_west_cav = pfp_north_west_cav.rename(columns={"Route": "Route March"})
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pfp_north_west_pv = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs "
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"rates/PFP_north_west_reviewed_standardised_15052025.xlsx",
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sheet_name="PV Route",
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header=1
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)
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pfp_north_west_pv = pfp_north_west_pv.rename(columns={"Route": "Route March"})
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pfp_north_west_cav["location"] = "North West"
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pfp_north_west_pv["location"] = "North West"
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cav_route = pd.concat(
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[
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pfp_london_cav,
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pfp_east_cav,
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pfp_north_east_cav,
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pfp_north_west_cav
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]
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)
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solar_route = pd.concat(
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[
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pfp_london_pv,
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pfp_east_pv,
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pfp_north_east_pv,
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pfp_north_west_pv
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]
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)
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def get_band(sap_score_number):
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bands = [
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("High_A", 96, float("inf")),
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("Low_A", 92, 96),
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("High_B", 86, 92),
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("Low_B", 81, 86),
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("High_C", 74.5, 81),
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("Low_C", 69, 74.5),
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("High_D", 61.5, 69),
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("Low_D", 55, 61.5),
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("High_E", 46.5, 55),
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("Low_E", 39, 46.5),
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("High_F", 29.5, 39),
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("Low_F", 21, 29.5),
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("High_G", 10.5, 21),
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("Low_G", 1, 10.5),
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]
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for band, lower, upper in bands:
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if lower <= sap_score_number < upper:
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return band
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return None
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def classify_floor_area(floor_area):
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if floor_area <= 72:
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return "0-72"
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if floor_area <= 97:
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return "73-97"
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if floor_area <= 199:
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return "98-199"
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return "200+"
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# We classify the abs bounds
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solar_route["starting_abs_band"] = solar_route["epc_sap_score_on_register"].apply(get_band)
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solar_route["ending_abs_band_scenario1"] = "High_C"
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solar_route["ending_abs_band_scenario2"] = "Low_B"
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solar_route["epc_total_floor_area"] = solar_route["epc_total_floor_area"].fillna(90)
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solar_route["floor_area_band"] = solar_route["epc_total_floor_area"].apply(classify_floor_area)
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# We classify the abs bounds
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cav_route["epc_sap_score_on_register"] = cav_route["epc_sap_score_on_register"].fillna(68)
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cav_route["starting_abs_band"] = cav_route["epc_sap_score_on_register"].apply(get_band)
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cav_route["floor_area_band"] = cav_route["epc_total_floor_area"].apply(classify_floor_area)
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cav_route["ending_abs_band"] = "Low_C"
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abs_matrix = pd.read_csv(
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"/Users/khalimconn-kowlessar/Downloads/ECO4 Full Project Scores Matrix.csv"
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)
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cav_route = cav_route.merge(
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abs_matrix.rename(columns={"Cost Savings": "ABS Rate"}),
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how="left",
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left_on=["starting_abs_band", "ending_abs_band", "floor_area_band"],
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right_on=["Starting Band", "Finishing Band", "Floor Area Segment"],
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)
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solar_route = solar_route.merge(
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abs_matrix.rename(columns={"Cost Savings": "ABS Rate"}),
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how="left",
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left_on=["starting_abs_band", "ending_abs_band_scenario1", "floor_area_band"],
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right_on=["Starting Band", "Finishing Band", "Floor Area Segment"],
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)
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cav_route["ABS Rate"] = cav_route["ABS Rate"].fillna(0)
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solar_route["ABS Rate"] = solar_route["ABS Rate"].fillna(0)
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cav_abs_agg = (
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cav_route.groupby("Route March").agg(
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{
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"ABS Rate": "sum",
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"landlord_property_id": "count",
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}
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).reset_index()
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)
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cav_abs_agg["Week Number"] = cav_abs_agg["Route March"].str.extract(r"(\d+)").astype(int)
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cav_abs_agg = cav_abs_agg.sort_values("Week Number", ascending=True)
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cav_abs_agg = cav_abs_agg.rename(columns={"landlord_property_id": "Number of Properties"})
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solar_abs_agg = (
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solar_route.groupby("Route March").agg(
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{
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"ABS Rate": "sum",
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"landlord_property_id": "count",
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}
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).reset_index()
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)
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solar_abs_agg["Week Number"] = solar_abs_agg["Route March"].str.extract(r"(\d+)").astype(int)
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solar_abs_agg = solar_abs_agg.rename(columns={"landlord_property_id": "Number of Properties"})
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solar_abs_agg = solar_abs_agg.sort_values("Week Number", ascending=True)
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# We store the data
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# Store as an excel
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filename = "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Places For People/abs rates/pfp programme rates.xlsx"
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# Store the data in two tabs. One for the asset list with the EPC data and the second with the flat data
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with pd.ExcelWriter(filename) as writer:
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solar_abs_agg.to_excel(writer, sheet_name="Solar ABS", index=False)
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cav_abs_agg.to_excel(writer, sheet_name="Cav ABS", index=False)
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cav_route.to_excel(writer, sheet_name="Cavity data", index=False)
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solar_route.to_excel(writer, sheet_name="Solar data", index=False)
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