code: def transform(self, X, y=None):
          
          if not X.columns.equals(self.columns_):
              raise ValueError(
                  "Columns of 'X' do not match the training "
                  "columns. Got {!r}, expected {!r}".format(X.columns, self.columns)
              )
          if isinstance(X, pd.DataFrame):
              return pd.get_dummies(X, drop_first=self.drop_first, columns=self.columns)
          elif isinstance(X, dd.DataFrame):
              return dd.get_dummies(X, drop_first=self.drop_first, columns=self.columns)
          else:
              raise TypeError("Unexpected type {}".format(type(X)))
docs: Dummy encode the categorical columns in X
  
          Parameters
          ----------
          X : pd.DataFrame or dd.DataFrame
          y : ignored
  
          Returns
          -------
          transformed : pd.DataFrame or dd.DataFrame
              Same type as the input