import polars as pl
from fe_polars.imputing.base_imputing import Imputer
from fe_polars.encoding.target_encoding import TargetEncoder

dataframe = pl.DataFrame(
        {
            "City": ["A", "A", "B", "B", "B", "C", "C", "C"],
            "Rain": [103, None, 90, 75, None, 200, 155, 127],
            "Temperature": [30.5, 32, 25, 38, 40, 29.6, 21.3, 24.9],
        }
    )

imputer = Imputer(features_to_impute=["Rain"], strategy="mean")
encoder = TargetEncoder(smoothing=2, features_to_encode=["City"])

temp = imputer.fit_transform(x=dataframe)
encoder.fit_transform(x=temp, y=dataframe['Temperature'])


shape: (8, 3)
City    Temperature Rain
f64     f64         f64

30.706  30.5        103.0
30.706  32.0        125.0
32.665  25.0        90.0
32.665  38.0        75.0
32.665  40.0        125.0
27.225  29.6        200.0
27.225  21.3        155.0
27.225  24.9        127.0