def _call_series()

in core/maxframe/dataframe/misc/apply.py [0:0]

• 70 lines of code
• 22 McCabe index (conditional complexity)

    def _call_series(self, series, dtypes=None, dtype=None, name=None, index=None):
        # for backward compatibility
        dtype = dtype if dtype is not None else dtypes
        if self.convert_dtype:
            if self.output_types is not None and (
                dtypes is not None or dtype is not None
            ):
                infer_series = test_series = None
            else:
                test_series = build_series(series, size=2, name=series.name)
                try:
                    with np.errstate(all="ignore"), quiet_stdio():
                        infer_series = test_series.apply(
                            self.func, args=self.args, **self.kwds
                        )
                except:  # noqa: E722  # nosec  # pylint: disable=bare-except
                    infer_series = None

            output_type = self._output_types[0]

            if index is not None:
                index_value = parse_index(index)
            elif infer_series is not None:
                if infer_series.index is test_series.index:
                    index_value = series.index_value
                else:  # pragma: no cover
                    index_value = parse_index(infer_series.index)
            else:
                index_value = parse_index(series.index_value)

            if output_type == OutputType.dataframe:
                if dtypes is None:
                    if infer_series is not None and infer_series.ndim == 2:
                        dtypes = infer_series.dtypes
                    else:
                        raise TypeError(
                            "Cannot determine dtypes, "
                            "please specify `dtypes` as argument"
                        )
                columns_value = parse_index(dtypes.index, store_data=True)

                return self.new_dataframe(
                    [series],
                    shape=(series.shape[0], len(dtypes)),
                    index_value=index_value,
                    columns_value=columns_value,
                    dtypes=dtypes,
                )
            else:
                if (
                    dtype is None
                    and infer_series is not None
                    and infer_series.ndim == 1
                ):
                    dtype = infer_series.dtype
                else:
                    dtype = dtype if dtype is not None else np.dtype(object)
                if infer_series is not None and infer_series.ndim == 1:
                    name = name or infer_series.name
                return self.new_series(
                    [series],
                    dtype=dtype,
                    shape=series.shape,
                    index_value=index_value,
                    name=name,
                )
        else:
            dtype = dtype if dtype is not None else np.dtype("object")
            return self.new_series(
                [series],
                dtype=dtype,
                shape=series.shape,
                index_value=series.index_value,
                name=name,
            )