code: def fit(self, X, column):
      self._old_column = column
      self._vectorizer = TfidfVectorizer(
          analyzer="word",
          stop_words="english",
          lowercase=True,
          max_features=self._max_features,
      )
  
      x = X[column][~pd.isnull(X[column])]
      self._vectorizer.fit(x)
      for f in list(self._vectorizer.get_feature_names_out()):
          new_col = self._old_column + "_" + f
          self._new_columns += [new_col]
  
file_path: mljar-supervised/supervised/preprocessing/text_transformer.py
imports: import datetime
  import json
  import warnings
  import numpy
  import pandas
  from sklearn.feature_extraction.text import TfidfVectorizer
label_desc: Use image node_id 2 for calling the TextTransformer obj's underlying member method code with example usage: obj.fit(X, column) without return types