Function _possibly_convert_objects

xarray/core/variable.py:211–242

Convert object arrays into datetime64 and timedelta64 according to the pandas convention. For backwards compat, as of 3.0.0 pandas, object dtype inputs are cast to strings by `pandas.Series` but we output them as object dtype with the input metadata preserved as well. * datetime.d

(values)

def _possibly_convert_objects(values):
    """Convert object arrays into datetime64 and timedelta64 according
    to the pandas convention.  For backwards compat, as of 3.0.0 pandas,
    object dtype inputs are cast to strings by `pandas.Series`
    but we output them as object dtype with the input metadata preserved as well.


    * datetime.datetime
    * datetime.timedelta
    * pd.Timestamp
    * pd.Timedelta
    """
    as_series = pd.Series(values.ravel(), copy=False)
    result = np.asarray(as_series).reshape(values.shape)
    if not result.flags.writeable:
        # GH8843, pandas copy-on-write mode creates read-only arrays by default
        try:
            result.flags.writeable = True
        except ValueError:
            result = result.copy()
    # For why we need this behavior: https://github.com/pandas-dev/pandas/issues/61938
    # Object datatype inputs that are strings
    # will be converted to strings by `pandas.Series`, and as of 3.0.0, lose
    # `dtype.metadata`.  If the roundtrip back to numpy in this function yields an
    # object array again, the dtype.metadata will be preserved.
    if (
        result.dtype.kind == "O"
        and values.dtype.kind == "O"
        and Version(pd.__version__) >= Version("3.0.0dev0")
    ):
        result = result.view(values.dtype)
    return result


def as_compatible_data(