fix json cases

Author: jbrockmendel

pandas/io/json/_json.py

@@ -1312,7 +1312,11 @@ def _try_convert_to_date(self, data: Series) -> Series:
         date_units = (self.date_unit,) if self.date_unit else self._STAMP_UNITS
         for date_unit in date_units:
             try:
-                return to_datetime(new_data, errors="raise", unit=date_unit)
+                # Without this as_unit cast, we would fail to overflow
+                #  and get much-too-large dates
+                return to_datetime(new_data, errors="raise", unit=date_unit).dt.as_unit(
+                    "ns"
+                )
             except (ValueError, OverflowError, TypeError):
                 continue
         return data

pandas/tests/io/json/test_pandas.py

@@ -964,7 +964,7 @@ def test_date_format_series(self, date, date_unit, datetime_series):
             json = ts.to_json(date_format="iso")
 
         result = read_json(StringIO(json), typ="series")
-        expected = ts.copy()
+        expected = ts.copy().dt.as_unit("ns")
         tm.assert_series_equal(result, expected)
 
     def test_date_format_series_raises(self, datetime_series):
@@ -1118,9 +1118,9 @@ def test_round_trip_exception(self, datapath):
     @pytest.mark.parametrize(
         "field,dtype",
         [
-            ["created_at", pd.DatetimeTZDtype(tz="UTC", unit="us")],
-            ["closed_at", "datetime64[us]"],
-            ["updated_at", pd.DatetimeTZDtype(tz="UTC", unit="us")],
+            ["created_at", pd.DatetimeTZDtype(tz="UTC")],
+            ["closed_at", "datetime64[ns]"],
+            ["updated_at", pd.DatetimeTZDtype(tz="UTC")],
         ],
     )
     def test_url(self, field, dtype, httpserver):
@@ -1756,7 +1756,7 @@ def test_read_timezone_information(self):
         result = read_json(
             StringIO('{"2019-01-01T11:00:00.000Z":88}'), typ="series", orient="index"
         )
-        exp_dti = DatetimeIndex(["2019-01-01 11:00:00"], dtype="M8[us, UTC]")
+        exp_dti = DatetimeIndex(["2019-01-01 11:00:00"], dtype="M8[ns, UTC]")
         expected = Series([88], index=exp_dti)
         tm.assert_series_equal(result, expected)