BUG to_timedelta was raising ValueError w pd.NA (pandas-dev#53022)

* BUG fixing timedelta

* BUG timedelta raising w pd.NA

* BUG removed not needed fail on test .. ?

* BUG Parametrised test

Author: DeaMariaLeon

doc/source/whatsnew/v2.0.2.rst

@@ -22,10 +22,11 @@ Bug fixes
 ~~~~~~~~~
 - Bug in :func:`api.interchange.from_dataframe` was returning :class:`DataFrame`'s of incorrect sizes when called on slices (:issue:`52824`)
 - Bug in :func:`api.interchange.from_dataframe` was unnecessarily raising on bitmasks (:issue:`49888`)
+- Bug in :func:`to_timedelta` was raising ``ValueError`` with ``pandas.NA`` (:issue:`52909`)
 - Bug in :meth:`DataFrame.convert_dtypes` ignores ``convert_*`` keywords when set to False ``dtype_backend="pyarrow"`` (:issue:`52872`)
 - Bug in :meth:`Series.describe` treating pyarrow-backed timestamps and timedeltas as categorical data (:issue:`53001`)
 - Bug in :meth:`pd.array` raising for ``NumPy`` array and ``pa.large_string`` or ``pa.large_binary`` (:issue:`52590`)
--
+
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_202.other:

pandas/_libs/tslibs/timedeltas.pyx

@@ -34,6 +34,7 @@ import_datetime()
 
 
 cimport pandas._libs.tslibs.util as util
+from pandas._libs.missing cimport checknull_with_nat_and_na
 from pandas._libs.tslibs.base cimport ABCTimestamp
 from pandas._libs.tslibs.conversion cimport (
     cast_from_unit,
@@ -341,8 +342,7 @@ cdef convert_to_timedelta64(object ts, str unit):
     Return an ns based int64
     """
     # Caller is responsible for checking unit not in ["Y", "y", "M"]
-
-    if checknull_with_nat(ts):
+    if checknull_with_nat_and_na(ts):
         return np.timedelta64(NPY_NAT, "ns")
     elif isinstance(ts, _Timedelta):
         # already in the proper format
@@ -1808,7 +1808,7 @@ class Timedelta(_Timedelta):
             # unit=None is de-facto 'ns'
             unit = parse_timedelta_unit(unit)
             value = convert_to_timedelta64(value, unit)
-        elif checknull_with_nat(value):
+        elif checknull_with_nat_and_na(value):
             return NaT
         else:
             raise ValueError(

pandas/tests/series/methods/test_astype.py

@@ -471,7 +471,7 @@ class TestAstypeString:
     def test_astype_string_to_extension_dtype_roundtrip(
         self, data, dtype, request, nullable_string_dtype
     ):
-        if dtype == "boolean" or (dtype == "timedelta64[ns]" and NaT in data):
+        if dtype == "boolean":
             mark = pytest.mark.xfail(
                 reason="TODO StringArray.astype() with missing values #GH40566"
             )

pandas/tests/tools/test_to_timedelta.py

@@ -214,11 +214,16 @@ def test_to_timedelta_on_missing_values(self):
         actual = to_timedelta(ser)
         tm.assert_series_equal(actual, expected)
 
-    @pytest.mark.parametrize("val", [np.nan, pd.NaT])
+    @pytest.mark.parametrize("val", [np.nan, pd.NaT, pd.NA])
     def test_to_timedelta_on_missing_values_scalar(self, val):
         actual = to_timedelta(val)
         assert actual._value == np.timedelta64("NaT").astype("int64")
 
+    @pytest.mark.parametrize("val", [np.nan, pd.NaT, pd.NA])
+    def test_to_timedelta_on_missing_values_list(self, val):
+        actual = to_timedelta([val])
+        assert actual[0]._value == np.timedelta64("NaT").astype("int64")
+
     def test_to_timedelta_float(self):
         # https://github.com/pandas-dev/pandas/issues/25077
         arr = np.arange(0, 1, 1e-6)[-10:]