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25 lines
885 B
Python
25 lines
885 B
Python
import pandas as pd
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def app():
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"""
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Pulling the list of EPC G & F properties in Birmingham for Goldman Sachs
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"""
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epc_data = pd.read_csv(
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"local_data/all-domestic-certificates/domestic-E08000025-Birmingham/certificates.csv",
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low_memory=False
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)
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epc_data = epc_data[~pd.isnull(epc_data["UPRN"])]
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epc_data["UPRN"] = epc_data["UPRN"].astype(int).astype(str)
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# Get the newest EPC for each UPRN. We use LODGEMENT_DATE as a proxy for this
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epc_data["LODGEMENT_DATETIME"] = pd.to_datetime(epc_data["LODGEMENT_DATETIME"], format='mixed')
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epc_data = epc_data.sort_values("LODGEMENT_DATETIME", ascending=False).drop_duplicates("UPRN")
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# Get G & F properties
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epc_data = epc_data[epc_data["CURRENT_ENERGY_RATING"].isin(["G", "F"])]
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# Save as an excel
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epc_data.to_excel("Birmingham EPC F & G Properties.xlsx", index=False)
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