perfect-postcode/pipeline/transform/merge.py

127 lines
4.6 KiB
Python

import argparse
import polars as pl
from pathlib import Path
def _build_wide(
epc_pp_path: Path,
arcgis_path: Path,
iod_path: Path | None,
poi_proximity_path: Path | None,
journey_times_path: Path | None,
) -> pl.DataFrame:
"""Build the wide dataframe by joining epc_pp with all auxiliary data."""
print("Loading epc_pp...")
wide = pl.read_parquet(epc_pp_path)
print(f" {wide.shape[0]:,} rows, {wide.estimated_size('mb'):.1f} MB")
# GPS coordinates + LSOA from ArcGIS
print("Joining GPS coordinates...")
arcgis = pl.read_parquet(arcgis_path).select(
pl.col("pcds").alias("postcode"),
"lat",
pl.col("long").alias("lon"),
"lsoa21",
)
wide = wide.join(arcgis, on="postcode", how="inner")
print(f" {wide.shape[0]:,} rows after GPS join, {wide.estimated_size('mb'):.1f} MB")
# Journey times (optional)
if journey_times_path and journey_times_path.exists():
print("Joining journey times...")
journey_times = pl.read_parquet(journey_times_path).select(
"postcode",
"public_transport_easy_minutes",
"public_transport_quick_minutes",
"cycling_minutes",
)
wide = wide.join(journey_times, on="postcode", how="left")
print(f" {wide.estimated_size('mb'):.1f} MB after journey times")
# Index of Deprivation
if iod_path and iod_path.exists():
print("Joining IoD scores...")
iod = pl.read_parquet(iod_path)
wide = wide.join(
iod, left_on="lsoa21", right_on="LSOA code (2021)", how="left"
)
print(f" {wide.estimated_size('mb'):.1f} MB after IoD")
# POI proximity counts (pre-computed per postcode)
if poi_proximity_path and poi_proximity_path.exists():
print("Joining POI proximity counts...")
poi_counts = pl.read_parquet(poi_proximity_path)
wide = wide.join(poi_counts, on="postcode", how="left")
print(f" {wide.estimated_size('mb'):.1f} MB after POI counts")
# Convert construction_age_band to numeric year
if "construction_age_band" in wide.columns:
wide = wide.with_columns(
pl.col("construction_age_band")
.str.replace("England and Wales: ", "")
.str.replace(" onwards", "")
.str.extract(r"(\d{4})", 1)
.cast(pl.UInt16, strict=False)
.alias("construction_age_band"),
)
# Derived columns
wide = wide.with_columns(
(pl.col("latest_price") / pl.col("total_floor_area")).alias("Price per sqm"),
).drop(
'date_of_transfer',
'inspection_date',
'floor_height',
'lsoa21',
'LSOA code (2021)',
'Local Authority District code (2024)',
'Local Authority District name (2024)',
'imd_score',
'housing_barriers_score',
'idaci_score',
'idaopi_score',
'children_young_people_score',
'adult_skills_score',
'geographical_barriers_score',
'wider_barriers_score',
).rename({
'construction_age_band': "Approximate construction age",
"income_score": "Income Score (rate)",
"employment_score": "Employment Score (rate)",
"education_score": "Education, Skills and Training Score",
"health_score": "Health Deprivation and Disability Score",
"crime_score": "Crime Score",
})
return wide
def main():
parser = argparse.ArgumentParser(description="Build wide property dataframe with all joins")
parser.add_argument("--epc-pp", type=Path, required=True, help="EPC-Price Paid joined parquet file")
parser.add_argument("--arcgis", type=Path, required=True, help="ArcGIS postcode data parquet file")
parser.add_argument("--iod", type=Path, help="Index of Deprivation parquet file (optional)")
parser.add_argument("--poi-proximity", type=Path, help="POI proximity counts parquet file (optional)")
parser.add_argument("--journey-times", type=Path, help="Journey times parquet file (optional)")
parser.add_argument("--output", type=Path, required=True, help="Output parquet file path")
args = parser.parse_args()
wide = _build_wide(
epc_pp_path=args.epc_pp,
arcgis_path=args.arcgis,
iod_path=args.iod,
poi_proximity_path=args.poi_proximity,
journey_times_path=args.journey_times,
)
print(f"Columns: {wide.columns}")
print(f"Rows: {wide.height}")
wide.write_parquet(args.output)
size_mb = args.output.stat().st_size / (1024 * 1024)
print(f"Wrote {args.output} ({size_mb:.1f} MB)")
if __name__ == "__main__":
main()