Method _wrap_result

pandas/core/strings/accessor.py:260–402

(
        self,
        result,
        name=None,
        expand: bool | None = None,
        fill_value=np.nan,
        returns_string: bool = True,
        dtype=None,
    )

        raise TypeError(f"'{type(self).__name__}' object is not iterable")

    def _wrap_result(
        self,
        result,
        name=None,
        expand: bool | None = None,
        fill_value=np.nan,
        returns_string: bool = True,
        dtype=None,
    ):
        from pandas import (
            Index,
            MultiIndex,
        )

        if not hasattr(result, "ndim") or not hasattr(result, "dtype"):
            if isinstance(result, ABCDataFrame):
                result = result.__finalize__(self._orig, name="str")
            return result
        assert result.ndim < 3

        # We can be wrapping a string / object / categorical result, in which
        # case we'll want to return the same dtype as the input.
        # Or we can be wrapping a numeric output, in which case we don't want
        # to return a StringArray.
        # Ideally the array method returns the right array type.
        if expand is None:
            # infer from ndim if expand is not specified
            expand = result.ndim != 1
        elif expand is True and not isinstance(self._orig, ABCIndex):
            # required when expand=True is explicitly specified
            # not needed when inferred
            if isinstance(result.dtype, ArrowDtype):
                import pyarrow as pa

                from pandas.core.arrays.arrow.array import ArrowExtensionArray

                value_lengths = pa.compute.list_value_length(result._pa_array)
                max_len = pa.compute.max(value_lengths).as_py()
                min_len = pa.compute.min(value_lengths).as_py()
                if result._hasna:
                    # ArrowExtensionArray.fillna doesn't work for list scalars
                    result = ArrowExtensionArray(
                        result._pa_array.fill_null([None] * max_len)
                    )
                if min_len < max_len:
                    # append nulls to each scalar list element up to max_len
                    result = ArrowExtensionArray(
                        pa.compute.list_slice(
                            result._pa_array,
                            start=0,
                            stop=max_len,
                            return_fixed_size_list=True,
                        )
                    )
                if name is None:
                    name = range(max_len)
                result = (
                    pa.compute.list_flatten(result._pa_array)