(self, variables=None, return_labels=False)
return matrix
Get the numeric computed statistics in a single matrix. Optionally,
        we can specify for which variables we want the stats. Also, we can get
        the string column names as labels if desired.

        Parameters
        ----------
        variables : Iterable[Union[Variable, int, str]]
            Return statistics for only the variables specified. Accepts all
            formats supported by `domain.index`
        return_labels : bool
            In addition to the statistics matrix, also return string labels for
            the columns of the matrix e.g. 'Mean' or 'Dispersion', as specified
            in `Columns`.

        Returns
        -------
        Union[Tuple[List[str], np.ndarray], np.ndarray]
Get the numeric computed statistics in a single matrix. Optionally,
        we can specify for which variables we want the stats. Also, we can get
        the string column names as labels if desired.
Get the numeric computed statistics in a single matrix . Optionally we can specify for which variables we want the stats . Also we can get the string column names as labels if desired .
def get_statistics_matrix(self, variables=None, return_labels=False):
        """Get the numeric computed statistics in a single matrix. Optionally,
        we can specify for which variables we want the stats. Also, we can get
        the string column names as labels if desired.

        Parameters
        ----------
        variables : Iterable[Union[Variable, int, str]]
            Return statistics for only the variables specified. Accepts all
            formats supported by `domain.index`
        return_labels : bool
            In addition to the statistics matrix, also return string labels for
            the columns of the matrix e.g. 'Mean' or 'Dispersion', as specified
            in `Columns`.

        Returns
        -------
        Union[Tuple[List[str], np.ndarray], np.ndarray]

        """
        if self.table is None:
            return np.atleast_2d([])

        # If a list of variables is given, select only corresponding stats
        # variables can be a list or array, pylint: disable=len-as-condition
        if variables is not None and len(variables) != 0:
            indices = [self.domain.index(var) for var in variables]
        else:
            indices = ...

        matrix = np.vstack((
            self._center[indices], self._median[indices],
            self._dispersion[indices],
            self._min[indices], self._max[indices], self._missing[indices],
        )).T

        # Return string labels for the returned matrix columns e.g. 'Mean',
        # 'Dispersion' if requested
        if return_labels:
            labels = [self.Columns.CENTER.name, self.Columns.MEDIAN.name,
                      self.Columns.DISPERSION.name,
                      self.Columns.MIN.name, self.Columns.MAX.name,
                      self.Columns.MISSING.name]
            return labels, matrix

        return matrix
def get_statistics_matrix ( self , variables = None , return_labels = False ) : if self . table is None : return np . atleast_2d ( [ ] ) # If a list of variables is given, select only corresponding stats # variables can be a list or array, pylint: disable=len-as-condition if variables is not None and len ( variables ) != 0 : indices = [ self . domain . index ( var ) for var in variables ] else : indices = ... matrix = np . vstack ( ( self . _center [ indices ] , self . _median [ indices ] , self . _dispersion [ indices ] , self . _min [ indices ] , self . _max [ indices ] , self . _missing [ indices ] , ) ) . T # Return string labels for the returned matrix columns e.g. 'Mean', # 'Dispersion' if requested if return_labels : labels = [ self . Columns . CENTER . name , self . Columns . MEDIAN . name , self . Columns . DISPERSION . name , self . Columns . MIN . name , self . Columns . MAX . name , self . Columns . MISSING . name ] return labels , matrix return matrix