BUG: Period[us] start_time off by 1 nanosecond

doc/source/whatsnew/v1.1.0.rst

@@ -105,6 +105,7 @@ Datetimelike
 - Bug in :class:`Timestamp` where constructing :class:`Timestamp` from ambiguous epoch time and calling constructor again changed :meth:`Timestamp.value` property (:issue:`24329`)
 - :meth:`DatetimeArray.searchsorted`, :meth:`TimedeltaArray.searchsorted`, :meth:`PeriodArray.searchsorted` not recognizing non-pandas scalars and incorrectly raising ``ValueError`` instead of ``TypeError`` (:issue:`30950`)
 - Bug in :class:`Timestamp` where constructing :class:`Timestamp` with dateutil timezone less than 128 nanoseconds before daylight saving time switch from winter to summer would result in nonexistent time (:issue:`31043`)
+- Bug in :meth:`Period.to_timestamp`, :meth:`Period.start_time` with microsecond frequency returning a timestamp one nanosecond earlier than the correct time (:issue:`31475`)
 
 Timedelta
 ^^^^^^^^^

pandas/_libs/tslibs/period.pyx

@@ -22,7 +22,7 @@ PyDateTime_IMPORT
 from pandas._libs.tslibs.np_datetime cimport (
     npy_datetimestruct, dtstruct_to_dt64, dt64_to_dtstruct,
     pandas_datetime_to_datetimestruct, check_dts_bounds,
-    NPY_DATETIMEUNIT, NPY_FR_D)
+    NPY_DATETIMEUNIT, NPY_FR_D, NPY_FR_us)
 
 cdef extern from "src/datetime/np_datetime.h":
     int64_t npy_datetimestruct_to_datetime(NPY_DATETIMEUNIT fr,
@@ -1186,6 +1186,13 @@ cdef int64_t period_ordinal_to_dt64(int64_t ordinal, int freq) except? -1:
     if ordinal == NPY_NAT:
         return NPY_NAT
 
+    if freq == 11000:
+        # Microsecond, avoid get_date_info to prevent floating point errors
+        pandas_datetime_to_datetimestruct(ordinal, NPY_FR_us, &dts)
+        check_dts_bounds(&dts)
+        # Equivalent: return ordinal * 1000
+        return dtstruct_to_dt64(&dts)
+
     get_date_info(ordinal, freq, &dts)
     check_dts_bounds(&dts)
     return dtstruct_to_dt64(&dts)

pandas/tests/scalar/period/test_asfreq.py

@@ -3,7 +3,7 @@
 from pandas._libs.tslibs.frequencies import INVALID_FREQ_ERR_MSG, _period_code_map
 from pandas.errors import OutOfBoundsDatetime
 
-from pandas import Period, offsets
+from pandas import Period, Timestamp, offsets
 
 
 class TestFreqConversion:
@@ -656,6 +656,23 @@ def test_conv_secondly(self):
 
         assert ival_S.asfreq("S") == ival_S
 
+    def test_conv_microsecond(self):
+        # GH#31475 Avoid floating point errors dropping the start_time to
+        #  before the beginning of the Period
+        per = Period("2020-01-30 15:57:27.576166", freq="U")
+        assert per.ordinal == 1580399847576166
+
+        start = per.start_time
+        expected = Timestamp("2020-01-30 15:57:27.576166")
+        assert start == expected
+        assert start.value == per.ordinal * 1000
+
+        per2 = Period("2300-01-01", "us")
+        with pytest.raises(OutOfBoundsDatetime, match="2300-01-01"):
+            per2.start_time
+        with pytest.raises(OutOfBoundsDatetime, match="2300-01-01"):
+            per2.end_time
+
     def test_asfreq_mult(self):
         # normal freq to mult freq
         p = Period(freq="A", year=2007)