# Feature Scaling
df["feature_scaled"] = df["col"]/ (df["col"].max())
# Min-max Scaling
df["minmax_scaled"] = (df["col"] - df["col"].min()) / (df["col"].max() - df["col"].min())
# Z-score
df["z_scaled"] = (df["col"] - df["col"].mean()) / df["col"].std()
# Alternative : Using scikit learn
from sklearn.preprocessing import MinMaxScaler, StandardScaler, PowerTransformer
minmax_scaler = MinMaxScaler()
standard_scaler = StandardScaler()
log_scaler = PowerTransformer()
your_scaler.fit(df[['col']])
df['scaled_col'] = your_scaler.transform(df[['col']])