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Load and process shelter data from the pipeline-ready CSV.
Schema: shelter_name, union, upazila, district, shelter_type, capacity
Source: data/raw/shelters/shelters_coxs_bazar_pipeline_ready.csv (610 records)
"""
import pandas as pd
import logging
from src.config import SHELTER_DATA_FILE, PROCESSED_SHELTERS, PROCESSED_DIR
logger = logging.getLogger(__name__)
EXPECTED_COLUMNS = [
"shelter_name", "union", "upazila", "district", "shelter_type", "capacity"
]
def load_shelters() -> pd.DataFrame:
"""
Load shelter CSV, validate schema, and return a clean DataFrame.
Also saves a processed GeoJSON stub (tabular, no geometry yet) for
downstream spatial joins with union boundaries.
Returns:
pd.DataFrame with 610 shelter records.
"""
logger.info("Loading shelter data...")
if not SHELTER_DATA_FILE.exists():
raise FileNotFoundError(
f"Shelter data file not found: {SHELTER_DATA_FILE}\n"
"Expected the pipeline-ready CSV at this path."
)
df = pd.read_csv(SHELTER_DATA_FILE)
logger.info(f"Loaded {len(df)} shelter records from {SHELTER_DATA_FILE.name}")
# ── Schema validation ─────────────────────────────────────────────────
missing = [c for c in EXPECTED_COLUMNS if c not in df.columns]
if missing:
raise ValueError(
f"Shelter CSV missing required columns: {missing}\n"
f"Found columns: {list(df.columns)}"
)
# ── Type enforcement ──────────────────────────────────────────────────
df["capacity"] = pd.to_numeric(df["capacity"], errors="coerce").fillna(0).astype(int)
# ── Strip whitespace from string columns ──────────────────────────────
for col in ["shelter_name", "union", "upazila", "district", "shelter_type"]:
df[col] = df[col].astype(str).str.strip()
# ── Summary stats ─────────────────────────────────────────────────────
total_capacity = df["capacity"].sum()
types = df["shelter_type"].value_counts().to_dict()
upazilas = sorted(df["upazila"].unique())
logger.info(f" Total capacity: {total_capacity:,}")
logger.info(f" Shelter types: {types}")
logger.info(f" Upazilas ({len(upazilas)}): {upazilas}")
# ── Save processed CSV ────────────────────────────────────────────────
PROCESSED_DIR.mkdir(parents=True, exist_ok=True)
processed_csv = PROCESSED_DIR / "shelters_processed.csv"
df.to_csv(processed_csv, index=False)
logger.info(f"Saved processed shelters → {processed_csv}")
return df
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
shelters = load_shelters()
print(f"\n✅ {len(shelters)} shelters loaded successfully")
print(f" Total capacity: {shelters['capacity'].sum():,}")
print(f" Types: {shelters['shelter_type'].nunique()}")
print(f" Upazilas: {shelters['upazila'].nunique()}")
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