BUG: get_loc with time object matching NaT micros (#35114)

Author: jbrockmendel

doc/source/whatsnew/v1.1.0.rst

@@ -978,6 +978,7 @@ Indexing
 - Bug in :meth:`DataFrame.loc` with dictionary of values changes columns with dtype of ``int`` to ``float`` (:issue:`34573`)
 - Bug in :meth:`Series.loc` when used with a :class:`MultiIndex` would raise an IndexingError when accessing a None value (:issue:`34318`)
 - Bug in :meth:`DataFrame.reset_index` and :meth:`Series.reset_index` would not preserve data types on an empty :class:`DataFrame` or :class:`Series` with a :class:`MultiIndex` (:issue:`19602`)
+- Bug in :class:`Series` and :class:`DataFrame` indexing with a ``time`` key on a :class:`DatetimeIndex` with ``NaT`` entries (:issue:`35114`)
 
 Missing
 ^^^^^^^

pandas/_libs/tslibs/fields.pyx

@@ -16,7 +16,6 @@ from pandas._config.localization import set_locale
 
 from pandas._libs.tslibs.ccalendar import MONTHS_FULL, DAYS_FULL
 from pandas._libs.tslibs.ccalendar cimport (
-    DAY_NANOS,
     get_days_in_month, is_leapyear, dayofweek, get_week_of_year,
     get_day_of_year, get_iso_calendar, iso_calendar_t,
     month_offset,
@@ -28,27 +27,6 @@ from pandas._libs.tslibs.nattype cimport NPY_NAT
 from pandas._libs.tslibs.strptime import LocaleTime
 
 
-def get_time_micros(const int64_t[:] dtindex):
-    """
-    Return the number of microseconds in the time component of a
-    nanosecond timestamp.
-
-    Parameters
-    ----------
-    dtindex : ndarray[int64_t]
-
-    Returns
-    -------
-    micros : ndarray[int64_t]
-    """
-    cdef:
-        ndarray[int64_t] micros
-
-    micros = np.mod(dtindex, DAY_NANOS, dtype=np.int64)
-    micros //= 1000
-    return micros
-
-
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def build_field_sarray(const int64_t[:] dtindex):

pandas/core/indexes/datetimes.py

@@ -6,7 +6,7 @@
 import numpy as np
 
 from pandas._libs import NaT, Period, Timestamp, index as libindex, lib, tslib
-from pandas._libs.tslibs import Resolution, fields, parsing, timezones, to_offset
+from pandas._libs.tslibs import Resolution, parsing, timezones, to_offset
 from pandas._libs.tslibs.offsets import prefix_mapping
 from pandas._typing import DtypeObj, Label
 from pandas.errors import InvalidIndexError
@@ -86,7 +86,6 @@ def _new_DatetimeIndex(cls, d):
         "tzinfo",
         "dtype",
         "to_pydatetime",
-        "_local_timestamps",
         "_has_same_tz",
         "_format_native_types",
         "date",
@@ -380,10 +379,22 @@ def union_many(self, others):
     # --------------------------------------------------------------------
 
     def _get_time_micros(self):
+        """
+        Return the number of microseconds since midnight.
+
+        Returns
+        -------
+        ndarray[int64_t]
+        """
         values = self.asi8
         if self.tz is not None and not timezones.is_utc(self.tz):
             values = self._data._local_timestamps()
-        return fields.get_time_micros(values)
+
+        nanos = values % (24 * 3600 * 1_000_000_000)
+        micros = nanos // 1000
+
+        micros[self._isnan] = -1
+        return micros
 
     def to_series(self, keep_tz=lib.no_default, index=None, name=None):
         """
@@ -1094,6 +1105,6 @@ def bdate_range(
     )
 
 
-def _time_to_micros(time):
-    seconds = time.hour * 60 * 60 + 60 * time.minute + time.second
-    return 1000000 * seconds + time.microsecond
+def _time_to_micros(time_obj: time) -> int:
+    seconds = time_obj.hour * 60 * 60 + 60 * time_obj.minute + time_obj.second
+    return 1_000_000 * seconds + time_obj.microsecond

pandas/tests/indexes/datetimes/test_indexing.py

@@ -471,6 +471,16 @@ def test_get_loc(self):
         with pytest.raises(NotImplementedError, match=msg):
             idx.get_loc(time(12, 30), method="pad")
 
+    def test_get_loc_time_nat(self):
+        # GH#35114
+        # Case where key's total microseconds happens to match iNaT % 1e6 // 1000
+        tic = time(minute=12, second=43, microsecond=145224)
+        dti = pd.DatetimeIndex([pd.NaT])
+
+        loc = dti.get_loc(tic)
+        expected = np.array([], dtype=np.intp)
+        tm.assert_numpy_array_equal(loc, expected)
+
     def test_get_loc_tz_aware(self):
         # https://github.com/pandas-dev/pandas/issues/32140
         dti = pd.date_range(