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f3350ab | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | from pathlib import Path
import pandas as pd
RAW_DIR = Path(__file__).parent.parent / "data" / "raw" / "skincare_products"
CLEAN_DIR = Path(__file__).parent / "data"
def add_prices():
# --- Dermstore: join on title to recover price + currency ---
clean = pd.read_csv(CLEAN_DIR / "dermstore_skincare_cleaned.csv")
if "price" not in clean.columns:
raw = pd.read_csv(RAW_DIR / "dermstore_data.csv", usecols=["title", "price", "currency"])
raw["title"] = raw["title"].str.strip()
raw = raw.drop_duplicates("title")
clean["title"] = clean["title"].str.strip()
clean = clean.merge(raw, on="title", how="left")
clean.to_csv(CLEAN_DIR / "dermstore_skincare_cleaned.csv", index=False)
print(f"Dermstore: {clean['price'].notna().sum()}/{len(clean)} produits avec prix")
else:
print("Dermstore: colonne price déjà présente, skip")
# --- LookFantastic: price existe mais format '£5.20', normaliser ---
clean = pd.read_csv(CLEAN_DIR / "lookfantastic_skincare_cleaned.csv")
if "currency" not in clean.columns:
clean["price"] = (
clean["price"]
.astype(str)
.str.replace("£", "", regex=False)
.str.strip()
)
clean["price"] = pd.to_numeric(clean["price"], errors="coerce")
clean["currency"] = "GBP"
clean.to_csv(CLEAN_DIR / "lookfantastic_skincare_cleaned.csv", index=False)
print(f"LookFantastic: {clean['price'].notna().sum()}/{len(clean)} produits avec prix")
else:
print("LookFantastic: colonne currency déjà présente, skip")
# --- Amazon: prix en INR, non fiables → null ---
clean = pd.read_csv(CLEAN_DIR / "amazon_skincare_cleaned.csv")
if "price" not in clean.columns:
clean["price"] = None
clean["currency"] = None
clean.to_csv(CLEAN_DIR / "amazon_skincare_cleaned.csv", index=False)
print(f"Amazon: {len(clean)} produits sans prix (INR source, non exploitable)")
else:
print("Amazon: colonne price déjà présente, skip")
if __name__ == "__main__":
add_prices()
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