use internal series methods for datetime describe (#30209)

Author: david-cortes

doc/source/whatsnew/v1.1.0.rst

@@ -18,6 +18,8 @@ Enhancements
 Other enhancements
 ^^^^^^^^^^^^^^^^^^
 
+- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
+  will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
 -
 -
 

pandas/core/generic.py

@@ -30,7 +30,7 @@
 
 from pandas._config import config
 
-from pandas._libs import NaT, Timestamp, iNaT, lib, properties
+from pandas._libs import Timestamp, iNaT, lib, properties
 from pandas._typing import (
     Axis,
     Dtype,
@@ -9640,18 +9640,11 @@ def describe_categorical_1d(data):
 
         def describe_timestamp_1d(data):
             # GH-30164
-            tz = data.dt.tz
-            asint = data.dropna().values.view("i8")
-            is_empty = asint.shape[0] == 0
             stat_index = ["count", "mean", "min"] + formatted_percentiles + ["max"]
             d = (
-                [
-                    asint.shape[0],
-                    Timestamp(asint.mean(), tz=tz) if not is_empty else NaT,
-                    Timestamp(asint.min(), tz=tz) if not is_empty else NaT,
-                ]
+                [data.count(), data.mean(), data.min()]
                 + data.quantile(percentiles).tolist()
-                + [Timestamp(asint.max(), tz=tz) if not is_empty else NaT]
+                + [data.max()]
             )
             return pd.Series(d, index=stat_index, name=data.name)