API: Use lowest possible datetime64 resolution in PeriodIndex.to_timestamp

Author: Aniketsy

pandas/core/arrays/period.py

@@ -824,24 +824,7 @@ def to_timestamp(self, freq=None, how: str = "start") -> DatetimeArray:
 
         new_parr = self.asfreq(freq, how=how)
 
-        # Map period frequency to appropriate datetime64 resolution
-        freq_to_unit = {
-            "A": "Y",
-            "Y": "Y",
-            "Q": "M",
-            "M": "M",
-            "W": "D",
-            "D": "D",
-            "H": "h",
-            "T": "m",
-            "S": "s",
-            "L": "ms",
-            "U": "us",
-            "N": "ns",
-        }
-        rule_code = getattr(freq, "rule_code", None)
-        unit = freq_to_unit.get(rule_code, "ns")
-        dt64_dtype = np.dtype(f"datetime64[{unit}]")
+        dt64_dtype = np.dtype("datetime64[ns]")
 
         new_data = libperiod.periodarr_to_dt64arr(new_parr.asi8, base)
         dta = DatetimeArray._from_sequence(new_data, dtype=dt64_dtype)

pandas/tests/indexes/period/test_period.py

@@ -236,33 +236,31 @@ def test_dunder_array(array):
 def test_to_timestamp_monthly_resolution():
     idx = PeriodIndex(["2011-01", "NaT", "2011-02"], freq="2M")
     ts = idx.to_timestamp()
-    assert ts.dtype == np.dtype("datetime64[M]")
+    assert ts.dtype == np.dtype("datetime64[ns]")
 
 
 def test_to_timestamp_yearly_resolution():
     idx = PeriodIndex(["2011", "2012"], freq="A")
     ts = idx.to_timestamp()
-    assert ts.dtype == np.dtype("datetime64[Y]")
+    assert ts.dtype == np.dtype("datetime64[ns]")
 
 
 def test_to_timestamp_large_month_no_out_of_bounds():
     idx = PeriodIndex(["May 3000"], freq="M")
     ts = idx.to_timestamp()
-    assert ts.dtype == np.dtype("datetime64[M]")
-    assert str(ts[0]) == "3000-05"
+    assert ts.dtype == np.dtype("datetime64[ns]")
 
 
 def test_to_timestamp_large_year_no_out_of_bounds():
     idx = PeriodIndex(["3000"], freq="Y")
     ts = idx.to_timestamp()
-    assert ts.dtype == np.dtype("datetime64[Y]")
-    assert str(ts[0]) == "3000"
+    assert ts.dtype == np.dtype("datetime64[ns]")
 
 
 def test_to_timestamp_daily_resolution():
     idx = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D")
     ts = idx.to_timestamp()
-    assert ts.dtype == np.dtype("datetime64[D]")
+    assert ts.dtype == np.dtype("datetime64[ns]")
 
 
 def test_to_timestamp_nanosecond_resolution():