🗓️ 04 — Date, Time, and Text Features

Date Features

df["order_date"] = pd.to_datetime(df["order_date"])

df["order_month"] = df["order_date"].dt.month
df["order_dayofweek"] = df["order_date"].dt.dayofweek
df["is_weekend"] = df["order_dayofweek"].isin([5, 6])

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Time Since Event

reference_date = pd.Timestamp("2026-01-01")
df["customer_age_days"] = (reference_date - df["signup_date"]).dt.days

Use reference dates carefully to avoid future leakage.

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Text Features

Simple text features:

df["review_length"] = df["review"].str.len()
df["word_count"] = df["review"].str.split().str.len()

Vectorized text features:

from sklearn.feature_extraction.text import TfidfVectorizer

vectorizer = TfidfVectorizer(max_features=5000, stop_words="english")

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➡️ 05-pipelines-and-leakage