127 lines
3.7 KiB
Python
127 lines
3.7 KiB
Python
import argparse
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import polars as pl
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from pathlib import Path
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from ..utils import fuzzy_join_on_postcode
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pl.Config.set_tbl_cols(-1)
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def main():
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parser = argparse.ArgumentParser(description="Fuzzy join EPC and Price Paid data")
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parser.add_argument(
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"--epc", type=Path, required=True, help="EPC certificates CSV file"
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)
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parser.add_argument(
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"--price-paid", type=Path, required=True, help="Price paid parquet file"
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)
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parser.add_argument(
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"--output", type=Path, required=True, help="Output parquet file path"
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)
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args = parser.parse_args()
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epc = (
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pl.scan_csv(args.epc)
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.select(
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pl.col("ADDRESS").alias("epc_address"),
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"POSTCODE",
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"CURRENT_ENERGY_RATING",
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"POTENTIAL_ENERGY_RATING",
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pl.col("PROPERTY_TYPE").alias("epc_property_type"),
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"BUILT_FORM",
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"INSPECTION_DATE",
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"TOTAL_FLOOR_AREA",
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"NUMBER_HABITABLE_ROOMS",
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"FLOOR_HEIGHT",
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"CONSTRUCTION_AGE_BAND",
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)
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.filter(pl.col("epc_address").is_not_null())
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.sort("INSPECTION_DATE", descending=True)
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.group_by("epc_address", "POSTCODE")
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.first()
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)
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print("EPC dataset")
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print(epc.head().collect())
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# https://www.gov.uk/guidance/about-the-price-paid-data
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property_type_map = {
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"D": "Detached",
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"S": "Semi-Detached",
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"T": "Terraced",
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"F": "Flats/Maisonettes",
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"O": "Other",
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}
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duration_map = {"F": "Freehold", "L": "Leasehold"}
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price_paid = (
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pl.scan_parquet(args.price_paid)
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.select(
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"price",
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"date_of_transfer",
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pl.col("property_type")
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.alias("pp_property_type")
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.replace(property_type_map),
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"postcode",
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"paon",
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"saon",
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"street",
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"locality",
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"town_city",
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pl.col("duration").replace(duration_map),
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)
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.filter(pl.col("pp_property_type") != "Other")
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.with_columns(
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pl.concat_str(
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[pl.col("saon"), pl.col("paon"), pl.col("street")],
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separator=" ",
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ignore_nulls=True,
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).alias("pp_address"),
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)
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.sort("date_of_transfer")
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.group_by("pp_address", "postcode", maintain_order=True)
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.agg(
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pl.struct(
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pl.col("date_of_transfer").dt.year().alias("year"),
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"price",
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).alias("historical_prices"),
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pl.col("pp_property_type").last(),
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pl.col("duration").last(),
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pl.col("price").last().alias("latest_price"),
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pl.col("date_of_transfer").last(),
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)
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).filter(pl.col("pp_address").is_not_null())
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print("Price paid dataset")
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print(price_paid.head().collect())
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joined = (
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fuzzy_join_on_postcode(
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left=price_paid,
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right=epc,
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left_address_col="pp_address",
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right_address_col="epc_address",
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left_postcode_col="postcode",
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right_postcode_col="POSTCODE",
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)
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.drop("POSTCODE")
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.collect()
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)
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matched = joined.filter(
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pl.col("epc_address").is_not_null() & pl.col("pp_address").is_not_null()
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)
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total = joined.height
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print(f"Unique properties: {total}")
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print(f"Matched: {matched.height} ({100 * matched.height / total:.1f}%)")
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print(f"Unmatched: {total - matched.height}")
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matched = matched.rename({col: col.lower() for col in joined.columns})
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print(matched.head())
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matched.write_parquet(args.output)
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print(f"Wrote {args.output}")
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if __name__ == "__main__":
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main()
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