def drop_dimension(self, dimensions):
        dimensions = [dimensions] if np.isscalar(dimensions) else dimensions
        dims = [d for d in self.kdims if d not in dimensions]
        dim_inds = [self.get_dimension_index(d) for d in dims]
        key_getter = itemgetter(*dim_inds)
        return self.clone([(key_getter(k), v) for k, v in self.data.items()],
                          kdims=dims)
Returns a new mapping with the named dimension(s) removed.
dataset/ETHPy150Open ioam/holoviews/holoviews/core/ndmapping.py/MultiDimensionalMapping.drop_dimension