COMPAT: make astype to datetime/timedelta types more robust (#19176)

closes #19116

Author: jreback

pandas/core/dtypes/cast.py

@@ -690,7 +690,7 @@ def astype_nansafe(arr, dtype, copy=True):
             raise ValueError('Cannot convert non-finite values (NA or inf) to '
                              'integer')
 
-    elif arr.dtype == np.object_ and np.issubdtype(dtype.type, np.integer):
+    elif is_object_dtype(arr.dtype) and np.issubdtype(dtype.type, np.integer):
         # work around NumPy brokenness, #1987
         return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
 
@@ -703,6 +703,19 @@ def astype_nansafe(arr, dtype, copy=True):
         dtype = np.dtype(dtype.name + "[ns]")
 
     if copy:
+
+        if arr.dtype == dtype:
+            return arr.copy()
+
+        # we handle datetimelikes with pandas machinery
+        # to be robust to the input type
+        elif is_datetime64_dtype(dtype):
+            from pandas import to_datetime
+            return to_datetime(arr).values
+        elif is_timedelta64_dtype(dtype):
+            from pandas import to_timedelta
+            return to_timedelta(arr).values
+
         return arr.astype(dtype)
     return arr.view(dtype)
 

pandas/tests/io/json/test_json_table_schema.py

@@ -499,7 +499,7 @@ def test_read_json_table_orient(self, index_nm, vals):
         tm.assert_frame_equal(df, result)
 
     @pytest.mark.parametrize("index_nm", [
-        None, "idx", pytest.param("index", marks=pytest.mark.xfail)])
+        None, "idx", "index"])
     @pytest.mark.parametrize("vals", [
         {'timedeltas': pd.timedelta_range('1H', periods=4, freq='T')},
         {'timezones': pd.date_range('2016-01-01', freq='d', periods=4,