Method describe_categorical

python/pyarrow/interchange/column.py:328–361

If the dtype is categorical, there are two options: - There are only values in the data buffer. - There is a separate non-categorical Column encoding categorical values. Raises TypeError if the dtype is not categorical Returns the dictionary with

(self)

    @property
    def describe_categorical(self) -> CategoricalDescription:
        """
        If the dtype is categorical, there are two options:
        - There are only values in the data buffer.
        - There is a separate non-categorical Column encoding categorical
          values.

        Raises TypeError if the dtype is not categorical

        Returns the dictionary with description on how to interpret the
        data buffer:
            - "is_ordered" : bool, whether the ordering of dictionary indices
                             is semantically meaningful.
            - "is_dictionary" : bool, whether a mapping of
                                categorical values to other objects exists
            - "categories" : Column representing the (implicit) mapping of
                             indices to category values (e.g. an array of
                             cat1, cat2, ...). None if not a dictionary-style
                             categorical.

        TBD: are there any other in-memory representations that are needed?
        """
        arr = self._col
        if not pa.types.is_dictionary(arr.type):
            raise TypeError(
                "describe_categorical only works on a column with "
                "categorical dtype!"
            )

        return {
            "is_ordered": self._col.type.ordered,
            "is_dictionary": True,
            "categories": _PyArrowColumn(arr.dictionary),
        }

    @property
    def describe_null(self) -> Tuple[ColumnNullType, Any]: