code: def transform(self, X, y=None):
      X = X[self.nlp_cols].copy()
      for c in self.nlp_cols:
          X[c] = X[c].astype(str).fillna(" ")
      X = X.apply(" ".join, axis=1).str.replace("[ ]+", " ", regex=True)
      return X.values.tolist()
  
file_path: autogluon/tabular/src/autogluon/tabular/models/lr/lr_preprocessing_utils.py
imports: from sklearn.base import BaseEstimator, TransformerMixin
  from autogluon.features.generators import OneHotEncoderFeatureGenerator
label_desc: Use image node_id 3 for calling the NlpDataPreprocessor obj's underlying member method code with example usage: obj.transform(X, y) and returns: X