original_docstring: Use a Z-score to detect anomolies.
  
          :param column: the column to use for the z-score analysis.
  
          :param threshold: the threshold above which a data point is considered
                            an outlier
  
          :return: indexes in to :obj:`data` rows (indexes of a dataframe) of the
                   outliers
  
          
docstring: Use a Z-score to detect anomolies.
docstring_tokens: Use a Z - score to detect anomolies .
code: def z_score(self, column: Union[int, str]) -> np.ndarray:
          """Use a Z-score to detect anomolies.
  
          :param column: the column to use for the z-score analysis.
  
          :param threshold: the threshold above which a data point is considered
                            an outlier
  
          :return: indexes in to :obj:`data` rows (indexes of a dataframe) of the
                   outliers
  
          """
          if isinstance(column, str):
              if not isinstance(self.data, pd.DataFrame):
                  raise DatasetError(
                      'Can not index numpy arrays as string column: {column}')
              column = self.data.columns.get_loc(column)
          # shape: (R, C)
          arr: np.ndarray = self.numpy
          z = np.abs(stats.zscore(arr[:, column]))
          return self._select_indicies(z, 3.)
code_tokens: def z_score ( self , column : Union [ int , str ] ) -> np . ndarray : if isinstance ( column , str ) : if not isinstance ( self . data , pd . DataFrame ) : raise DatasetError ( 'Can not index numpy arrays as string column: {column}' ) column = self . data . columns . get_loc ( column ) arr : np . ndarray = self . numpy z = np . abs ( stats . zscore ( arr [ : , column ] ) ) return self . _select_indicies ( z , 3. )
short_docstring: Use a Z-score to detect anomolies.
short_docstring_tokens: Use a Z - score to detect anomolies .
comment: """Use a Z-score to detect anomolies.
  
          :param column: the column to use for the z-score analysis.
  
          :param threshold: the threshold above which a data point is considered
                            an outlier
  
          :return: indexes in to :obj:`data` rows (indexes of a dataframe) of the
                   outliers
  
          """$SEP$# shape: (R, C)