(self, col_vars=None, row_var=None)
Compute contingency matrices for one or more discrete or
        continuous variables against the specified discrete variable.

        The resulting list  contains a pair for each column variable.
        The first element contains the contingencies and the second
        elements gives the distribution of the row variables for instances
        in which the value of the column variable is missing.

        The format of contingencies returned depends on the variable type:

        - for discrete variables, it is a numpy array, where
          element (i, j) contains count of rows with i-th value of the
          row variable and j-th value of the column variable.

        - for continuous variables, contingency is a list of two arrays,
          where the first array contains ordered distinct values of the
          column_variable and the element (i,j) of the second array
          contains count of rows with i-th value of the row variable
          and j-th value of the ordered column variable.

        :param col_vars: variables whose values will correspond to columns of
            contingency matrices
        :type col_vars: list of ints, variable names or descriptors of type
            :obj:`Orange.data.Variable`
        :param row_var: a discrete variable whose values will correspond to the
            rows of contingency matrices
        :type row_var: int, variable name or :obj:`Orange.data.DiscreteVariable`
Compute contingency matrices for one or more discrete or
        continuous variables against the specified discrete variable.
Compute contingency matrices for one or more discrete or continuous variables against the specified discrete variable .
def _compute_contingency(self, col_vars=None, row_var=None):
        """
        Compute contingency matrices for one or more discrete or
        continuous variables against the specified discrete variable.

        The resulting list  contains a pair for each column variable.
        The first element contains the contingencies and the second
        elements gives the distribution of the row variables for instances
        in which the value of the column variable is missing.

        The format of contingencies returned depends on the variable type:

        - for discrete variables, it is a numpy array, where
          element (i, j) contains count of rows with i-th value of the
          row variable and j-th value of the column variable.

        - for continuous variables, contingency is a list of two arrays,
          where the first array contains ordered distinct values of the
          column_variable and the element (i,j) of the second array
          contains count of rows with i-th value of the row variable
          and j-th value of the ordered column variable.

        :param col_vars: variables whose values will correspond to columns of
            contingency matrices
        :type col_vars: list of ints, variable names or descriptors of type
            :obj:`Orange.data.Variable`
        :param row_var: a discrete variable whose values will correspond to the
            rows of contingency matrices
        :type row_var: int, variable name or :obj:`Orange.data.DiscreteVariable`
        """
        raise NotImplementedError
def _compute_contingency ( self , col_vars = None , row_var = None ) : raise NotImplementedError