Fix

Author: Chris Bertinato

pandas/io/parsers.py

@@ -3141,28 +3141,18 @@ def _get_lines(self, rows=None):
 def _make_date_converter(date_parser=None, dayfirst=False,
                          infer_datetime_format=False):
     def converter(*date_cols):
-        from pandas.core.dtypes.common import is_datetime64_dtype
         if date_parser is None:
             strs = _concat_date_cols(date_cols)
 
             try:
-                dti = tools.to_datetime(
+                return tools.to_datetime(
                     ensure_object(strs),
                     utc=None,
                     dayfirst=dayfirst,
                     errors='ignore',
                     infer_datetime_format=infer_datetime_format
-                )
-
-                if isinstance(dti, DatetimeIndex):
-                    dti = dti.to_pydatetime()
-                # elif is_datetime64_dtype(dti):
-                #     dti = np.array([Timestamp(ts).to_pydatetime()
-                #                     for ts in dti])
-                else:
-                    dti = dti.to_numpy()
+                ).to_numpy()
 
-                return dti
             except ValueError:
                 return tools.to_datetime(
                     parsing.try_parse_dates(strs, dayfirst=dayfirst))

pandas/tests/indexes/datetimes/test_tools.py

@@ -358,47 +358,43 @@ def test_to_datetime_dt64s(self, cache):
     def test_to_datetime_array_of_dt64s(self, cache):
         dts = [np.datetime64('2000-01-01'), np.datetime64('2000-01-02'), ]
 
-        with tm.assert_produces_warning(FutureWarning):
-
-            # Assuming all datetimes are in bounds, to_datetime() returns
-            # an array that is equal to Timestamp() parsing
-            tm.assert_numpy_array_equal(
-                pd.to_datetime(dts, box=False, cache=cache),
-                np.array([Timestamp(x).asm8 for x in dts])
-            )
+        # Assuming all datetimes are in bounds, to_datetime() returns
+        # an array that is equal to Timestamp() parsing
+        tm.assert_numpy_array_equal(
+            pd.to_datetime(dts, cache=cache).to_numpy(),
+            np.array([Timestamp(x).asm8 for x in dts])
+        )
 
-            # A list of datetimes where the last one is out of bounds
-            dts_with_oob = dts + [np.datetime64('9999-01-01')]
+        # A list of datetimes where the last one is out of bounds
+        dts_with_oob = dts + [np.datetime64('9999-01-01')]
 
-            pytest.raises(ValueError, pd.to_datetime, dts_with_oob,
-                          errors='raise')
+        with pytest.raises(ValueError):
+            pd.to_datetime(dts_with_oob)
 
-        with tm.assert_produces_warning(FutureWarning):
-            tm.assert_numpy_array_equal(
-                pd.to_datetime(dts_with_oob, box=False, errors='coerce',
-                               cache=cache),
-                np.array(
-                    [
-                        Timestamp(dts_with_oob[0]).asm8,
-                        Timestamp(dts_with_oob[1]).asm8,
-                        tslib.iNaT,
-                    ],
-                    dtype='M8'
-                )
+        tm.assert_numpy_array_equal(
+            pd.to_datetime(dts_with_oob, errors='coerce',
+                           cache=cache).to_numpy(),
+            np.array(
+                [
+                    Timestamp(dts_with_oob[0]).asm8,
+                    Timestamp(dts_with_oob[1]).asm8,
+                    tslib.iNaT,
+                ],
+                dtype='M8'
             )
-
-        with tm.assert_produces_warning(FutureWarning):
-            # With errors='ignore', out of bounds datetime64s
-            # are converted to their .item(), which depending on the version of
-            # numpy is either a python datetime.datetime or datetime.date
-            tm.assert_numpy_array_equal(
-                pd.to_datetime(dts_with_oob, box=False, errors='ignore',
-                               cache=cache),
-                np.array(
-                    [dt.item() for dt in dts_with_oob],
-                    dtype='O'
-                )
+        )
+
+        # With errors='ignore', out of bounds datetime64s
+        # are converted to their .item(), which depending on the version of
+        # numpy is either a python datetime.datetime or datetime.date
+        tm.assert_numpy_array_equal(
+            pd.to_datetime(dts_with_oob, errors='ignore',
+                           cache=cache).to_numpy(),
+            np.array(
+                [dt.item() for dt in dts_with_oob],
+                dtype='O'
             )
+        )
 
     @pytest.mark.parametrize('cache', [True, False])
     def test_to_datetime_tz(self, cache):