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71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
"""
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Rough script to get the EPC data for Benyon
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"""
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import pandas as pd
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import os
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from dotenv import load_dotenv
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from backend.SearchEpc import SearchEpc
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from asset_list.utils import get_data
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load_dotenv(dotenv_path="backend/.env")
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EPC_AUTH_TOKEN = os.getenv("EPC_AUTH_TOKEN")
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asset_list = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Benyon Estate/List of All Properties ecl Grd Rents in "
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"Alphabetical Order.xlsx",
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header=1
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)
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asset_list.columns = ["tennancy", "landlord_id", "landlord_address"]
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# Get postcode as the last 2 parts of the address, split on space
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asset_list["postcode"] = asset_list["landlord_address"].apply(lambda x: x.split(" ")[-2] + " " + x.split(" ")[-1])
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asset_list["house_no"] = asset_list.apply(
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lambda x: SearchEpc.get_house_number(address=x["landlord_address"], postcode=x["postcode"]), axis=1
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)
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epc_data, errors, no_epc = get_data(
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df=asset_list,
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manual_uprn_map={},
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epc_auth_token=EPC_AUTH_TOKEN,
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uprn_column=None,
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fulladdress_column="landlord_address",
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address1_column="house_no",
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postcode_column="postcode",
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property_type_column=None,
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built_form_column=None,
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epc_api_only=True,
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row_id_name="landlord_id",
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)
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df = asset_list[asset_list["landlord_id"].isin(no_epc)]
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epc_df = pd.DataFrame(epc_data)
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epc_df["current-energy-rating"].value_counts()
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epc_df["property-type"].value_counts()
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epc_df["walls-description"].value_counts(normalize=True)
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asset_list = asset_list.merge(
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epc_df[
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[
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"landlord_id", "current-energy-rating", "property-type", "total-floor-area", "roof-description",
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"walls-description", "co2-emissions-current"
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]
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],
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how="left",
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left_on="landlord_id",
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right_on="landlord_id"
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)
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asset_list.to_csv(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Benyon Estate/asset_list.csv", index=False
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)
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asset_list_big = asset_list.merge(
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epc_df,
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how="left",
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left_on="landlord_id",
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right_on="landlord_id"
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)
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asset_list_big.to_csv(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Benyon Estate/asset_list_full_data.csv",
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index=False
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)
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