BUG: close #30050 - initial solution

Author: AlexKirko

doc/source/whatsnew/v1.0.0.rst

@@ -796,6 +796,7 @@ Datetimelike
 - Bug in :meth:`DataFrame.append` would remove the timezone-awareness of new data (:issue:`30238`)
 - Bug in :meth:`Series.cummin` and :meth:`Series.cummax` with timezone-aware dtype incorrectly dropping its timezone (:issue:`15553`)
 - Bug in :class:`DatetimeArray`, :class:`TimedeltaArray`, and :class:`PeriodArray` where inplace addition and subtraction did not actually operate inplace (:issue:`24115`)
+- Bug in :func:`pandas.to_datetime` when called with ``Series`` storing ``IntegerArray`` raising ``TypeError`` instead of returning ``Series`` (:issue:`30050`)
 
 Timedelta
 ^^^^^^^^^

pandas/core/tools/datetimes.py

@@ -38,6 +38,8 @@
 )
 from pandas.core.dtypes.missing import notna
 
+from pandas._typing import ArrayLike
+from pandas.arrays import IntegerArray
 from pandas.core import algorithms
 from pandas.core.algorithms import unique
 
@@ -317,7 +319,20 @@ def _convert_listlike_datetimes(
         if format is not None:
             raise ValueError("cannot specify both format and unit")
         arg = getattr(arg, "values", arg)
-        result, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
+        # GH 30050 pass an ndarray to tslib.array_with_unit_to_datetime
+        # because it expects an ndarray argument
+        if isinstance(arg, IntegerArray):
+            arg_np = np.array(arg[np.logical_not(arg._mask)], dtype=type(arg[0]))
+            result_np, tz_parsed = tslib.array_with_unit_to_datetime(
+                arg_np, unit, errors=errors
+            )
+            result = np.empty(arg.shape[0], dtype="datetime64[" + unit + "]")
+            result[arg._mask] = np.datetime64("nat")
+            result[np.logical_not(arg._mask)] = result_np
+        else:
+            result, tz_parsed = tslib.array_with_unit_to_datetime(
+                arg, unit, errors=errors
+            )
         if errors == "ignore":
             from pandas import Index
 

pandas/tests/indexes/datetimes/test_tools.py

@@ -2291,3 +2291,21 @@ def test_should_cache_errors(unique_share, check_count, err_message):
 
     with pytest.raises(AssertionError, match=err_message):
         tools.should_cache(arg, unique_share, check_count)
+
+def test_intarray_to_datetime():
+    # Test for #30050
+    ser = pd.Series([1, 2, None, 2 ** 61, None])
+    ser = ser.astype("Int64")
+
+    res = pd.to_datetime(ser, unit="ns")
+
+    expected = pd.Series(
+        [
+            np.datetime64("1970-01-01 00:00:00.000000001"),
+            np.datetime64("1970-01-01 00:00:00.000000002"),
+            np.datetime64("NaT"),
+            np.datetime64("2043-01-25 23:56:49.213693952"),
+            np.datetime64("NaT"),
+        ]
+    )
+    tm.assert_series_equal(res, expected)