TYP: tighter typing in _maybe_convert_freq, _from_ordinal

pandas/_libs/tslibs/period.pyi

@@ -87,7 +87,7 @@ class Period(PeriodMixin):
     @classmethod
     def _maybe_convert_freq(cls, freq) -> BaseOffset: ...
     @classmethod
-    def _from_ordinal(cls, ordinal: int, freq) -> Period: ...
+    def _from_ordinal(cls, ordinal: int, freq: BaseOffset) -> Period: ...
     @classmethod
     def now(cls, freq: Frequency) -> Period: ...
     def strftime(self, fmt: str | None) -> str: ...

pandas/_libs/tslibs/period.pyx

@@ -1756,21 +1756,12 @@ cdef class _Period(PeriodMixin):
     @classmethod
     def _maybe_convert_freq(cls, object freq) -> BaseOffset:
         """
-        Internally we allow integer and tuple representations (for now) that
-        are not recognized by to_offset, so we convert them here.  Also, a
-        Period's freq attribute must have `freq.n > 0`, which we check for here.
+        A Period's freq attribute must have `freq.n > 0`, which we check for here.
 
         Returns
         -------
         DateOffset
         """
-        if isinstance(freq, int):
-            # We already have a dtype code
-            dtype = PeriodDtypeBase(freq, 1)
-            freq = dtype._freqstr
-        elif isinstance(freq, PeriodDtypeBase):
-            freq = freq._freqstr
-
         freq = to_offset(freq, is_period=True)
 
         if freq.n <= 0:
@@ -1780,7 +1771,7 @@ cdef class _Period(PeriodMixin):
         return freq
 
     @classmethod
-    def _from_ordinal(cls, ordinal: int64_t, freq) -> "Period":
+    def _from_ordinal(cls, ordinal: int64_t, freq: BaseOffset) -> "Period":
         """
         Fast creation from an ordinal and freq that are already validated!
         """
@@ -1988,8 +1979,10 @@ cdef class _Period(PeriodMixin):
             return endpoint - np.timedelta64(1, "ns")
 
         if freq is None:
-            freq = self._dtype._get_to_timestamp_base()
-            base = freq
+            freq_code = self._dtype._get_to_timestamp_base()
+            dtype = PeriodDtypeBase(freq_code, 1)
+            freq = dtype._freqstr
+            base = freq_code
         else:
             freq = self._maybe_convert_freq(freq)
             base = freq._period_dtype_code
@@ -2836,7 +2829,8 @@ class Period(_Period):
                 FutureWarning,
                 stacklevel=find_stack_level(),
             )
-
+        if ordinal == NPY_NAT:
+            return NaT
         return cls._from_ordinal(ordinal, freq)
 
 

pandas/core/arrays/period.py

@@ -35,6 +35,7 @@
 )
 from pandas._libs.tslibs.dtypes import (
     FreqGroup,
+    PeriodDtypeBase,
     freq_to_period_freqstr,
 )
 from pandas._libs.tslibs.fields import isleapyear_arr
@@ -652,8 +653,10 @@ def to_timestamp(self, freq=None, how: str = "start") -> DatetimeArray:
                 return (self + self.freq).to_timestamp(how="start") - adjust
 
         if freq is None:
-            freq = self._dtype._get_to_timestamp_base()
-            base = freq
+            freq_code = self._dtype._get_to_timestamp_base()
+            dtype = PeriodDtypeBase(freq_code, 1)
+            freq = dtype._freqstr
+            base = freq_code
         else:
             freq = Period._maybe_convert_freq(freq)
             base = freq._period_dtype_code

pandas/tests/scalar/period/test_period.py

@@ -418,7 +418,7 @@ def test_parse_week_str_roundstrip(self):
 
     def test_period_from_ordinal(self):
         p = Period("2011-01", freq="M")
-        res = Period._from_ordinal(p.ordinal, freq="M")
+        res = Period._from_ordinal(p.ordinal, freq=p.freq)
         assert p == res
         assert isinstance(res, Period)