A label enconding transformer

some_transformers.py

from sklearn.base import BaseEstimator, TransformerMixin


class NoFitMixin:
    """Gives fit method by inheritance."""
    def fit(self, X, y=None, **fit_params):
        return self


class LabelFeaturizer(BaseEstimator, TransformerMixin, NoFitMixin):
    """
    Transformer which converts given columns to 
    pandas category type and creates another column
    with the counts for the respective category.
    """
    def __init__(self, columns):
        self.columns = columns
        self.count_dict = {}

    def transform(self, df):
        df_ = df.copy()

        for column in self.columns:
            df_[column] = df[column].astype("category").cat.codes
            df_[column] = df_[column].astype("category")
            self.count_dict[column] = df_[column].value_counts().to_dict()
            df_[column + "_label_count"] = df[column].apply(lambda x: self.count_dict[column].get(x, 1))

        return df_