code: def fit(self, X):
          
          LOGGER.debug('Fitting Gaussian Copula')
          column_names = self.get_column_names(X)
          distribution_class = import_object(self.distribution)
  
          for column_name in column_names:
              self.distribs[column_name] = distribution_class()
              column = self.get_column(X, column_name)
              self.distribs[column_name].fit(column)
  
          self.covariance = self._get_covariance(X)
          self.fitted = True
docs: Compute the distribution for each variable and then its covariance matrix.
  
          Args:
              X(numpy.ndarray or pandas.DataFrame): Data to model.
  
          Returns:
              None