def nested_data_to_arrays( data: Sequence, columns: Index | None, index: Index | None, dtype: DtypeObj | None, ) -> tuple[list[ArrayLike], Index, Index]: """ Convert a single sequence of arrays to multiple arrays. """ # By the time we get here we have already checked treat_as_nested(data) if is_named_tuple(data[0]) and columns is None: columns = ensure_index(data[0]._fields) arrays, columns = to_arrays(data, columns, dtype=dtype) columns = ensure_index(columns) if index is None: if isinstance(data[0], ABCSeries): index = _get_names_from_index(data) elif isinstance(data[0], Categorical): # GH#38845 hit in test_constructor_categorical index = default_index(len(data[0])) else: index = default_index(len(data)) return arrays, columns, index
def nested_data_to_arrays( data: Sequence, columns: Optional[Index], index: Optional[Index], dtype: Optional[DtypeObj], ): """ Convert a single sequence of arrays to multiple arrays. """ # By the time we get here we have already checked treat_as_nested(data) if is_named_tuple(data[0]) and columns is None: columns = data[0]._fields arrays, columns = to_arrays(data, columns, dtype=dtype) columns = ensure_index(columns) if index is None: if isinstance(data[0], ABCSeries): index = _get_names_from_index(data) elif isinstance(data[0], Categorical): index = ibase.default_index(len(data[0])) else: index = ibase.default_index(len(data)) return arrays, columns, index