DOC: updated offset methods sec, min, h,d (#54427)

Author: dullibri

pandas/_libs/tslibs/offsets.pyx

@@ -1104,18 +1104,19 @@ cdef class Day(Tick):
     Examples
     --------
     You can use the parameter ``n`` to represent a shift of n days.
+
     >>> from pandas.tseries.offsets import Day
     >>> ts = pd.Timestamp(2022, 12, 9, 15)
-    >>> ts.strftime('%a %d %b %Y %H:%M')
-    'Fri 09 Dec 2022 15:00'
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
 
-    >>> (ts + Day()).strftime('%a %d %b %Y %H:%M')
-    'Sat 10 Dec 2022 15:00'
-    >>> (ts - Day(4)).strftime('%a %d %b %Y %H:%M')
-    'Mon 05 Dec 2022 15:00'
+    >>> ts + Day()
+    Timestamp('2022-12-10 15:00:00')
+    >>> ts - Day(4)
+    Timestamp('2022-12-05 15:00:00')
 
-    >>> (ts + Day(-4)).strftime('%a %d %b %Y %H:%M')
-    'Mon 05 Dec 2022 15:00'
+    >>> ts + Day(-4)
+    Timestamp('2022-12-05 15:00:00')
     """
     _nanos_inc = 24 * 3600 * 1_000_000_000
     _prefix = "D"
@@ -1142,16 +1143,16 @@ cdef class Hour(Tick):
 
     >>> from pandas.tseries.offsets import Hour
     >>> ts = pd.Timestamp(2022, 12, 9, 15)
-    >>> ts.strftime('%a %d %b %Y %H:%M')
-    'Fri 09 Dec 2022 15:00'
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
 
-    >>> (ts + Hour()).strftime('%a %d %b %Y %H:%M')
-    'Fri 09 Dec 2022 16:00'
-    >>> (ts - Hour(4)).strftime('%a %d %b %Y %H:%M')
-    'Fri 09 Dec 2022 11:00'
+    >>> ts + Hour()
+    Timestamp('2022-12-09 16:00:00')
+    >>> ts - Hour(4)
+    Timestamp('2022-12-09 11:00:00')
 
-    >>> (ts + Hour(-4)).strftime('%a %d %b %Y %H:%M')
-    'Fri 09 Dec 2022 11:00'
+    >>> ts + Hour(-4)
+    Timestamp('2022-12-09 11:00:00')
     """
     _nanos_inc = 3600 * 1_000_000_000
     _prefix = "H"
@@ -1178,16 +1179,16 @@ cdef class Minute(Tick):
 
     >>> from pandas.tseries.offsets import Minute
     >>> ts = pd.Timestamp(2022, 12, 9, 15)
-    >>> ts.strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 15:00:00'
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
 
-    >>> (ts + Minute(n=10)).strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 15:10:00'
-    >>> (ts - Minute(n=10)).strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 14:50:00'
+    >>> ts + Minute(n=10)
+    Timestamp('2022-12-09 15:10:00')
+    >>> ts - Minute(n=10)
+    Timestamp('2022-12-09 14:50:00')
 
-    >>> (ts + Minute(n=-10)).strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 14:50:00'
+    >>> ts + Minute(n=-10)
+    Timestamp('2022-12-09 14:50:00')
     """
     _nanos_inc = 60 * 1_000_000_000
     _prefix = "T"
@@ -1214,16 +1215,16 @@ cdef class Second(Tick):
 
     >>> from pandas.tseries.offsets import Second
     >>> ts = pd.Timestamp(2022, 12, 9, 15)
-    >>> ts.strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 15:00:00'
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
 
-    >>> (ts + Second(n=10)).strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 15:00:10'
-    >>> (ts - Second(n=10)).strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 14:59:50'
+    >>> ts + Second(n=10)
+    Timestamp('2022-12-09 15:00:10')
+    >>> ts - Second(n=10)
+    Timestamp('2022-12-09 14:59:50')
 
-    >>> (ts + Second(n=-10)).strftime('%a %d %b %Y %H:%M:%S')
-    'Fri 09 Dec 2022 14:59:50'
+    >>> ts + Second(n=-10)
+    Timestamp('2022-12-09 14:59:50')
     """
     _nanos_inc = 1_000_000_000
     _prefix = "S"