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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _pruning_base(self, axis=None, hs_dims=None):
 """Gets margin if across CAT dimension. Gets counts if across items. Categorical variables are pruned based on their marginal values. If the marginal is a 0 or a NaN, the corresponding row/column is pruned. In case of a subvars (items) dimension, we only prune if all the counts of the corresponding row/column are zero. """

        if not self._is_axis_allowed(axis):
            # In case we encountered axis that would go across items dimension,
            # we need to return at least some result, to prevent explicitly
            # checking for this condition, wherever self._margin is used
            return self.as_array(weighted=False, include_transforms_for_dims=hs_dims)

        # In case of allowed axis, just return the normal API margin. This call
        # would throw an exception when directly invoked with bad axis. This is
        # intended, because we want to be as explicit as possible. Margins
        # across items are not allowed.
        return self.margin(
            axis=axis, weighted=False, include_transforms_for_dims=hs_dims
        )