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
