Try to fix Summary should fit in a single line

Author: cloudboat

pandas/core/arrays/datetimelike.py

@@ -908,6 +908,7 @@ def freqstr(self) -> str | None:
     def inferred_freq(self) -> str | None:
         """
         Tries to return a string representing a frequency generated by infer_freq.
+
         Returns None if it can't autodetect the frequency.
 
         See Also

pandas/core/indexes/datetimelike.py

@@ -138,34 +138,30 @@ def mean(self, *, skipna: bool = True, axis: int | None = 0):
     @property
     def freq(self) -> BaseOffset | None:
         """
-        Return the frequency object as a string if it's set, otherwise None.
+        Return the frequency object if it is set, otherwise None.
+
+        To learn more about the frequency strings, please see
+        :ref:`this link<timeseries.offset_aliases>`.
 
         See Also
         --------
-        DatetimeIndex.inferred_freq : Returns a string representing a frequency
-            generated by infer_freq.
+        DatetimeIndex.freq : Return the frequency object if it is set, otherwise None.
+        PeriodIndex.freq : Return the frequency object if it is set, otherwise None.
 
         Examples
         --------
-        For DatetimeIndex:
-
-        >>> idx = pd.DatetimeIndex(["1/1/2020 10:00:00+00:00"], freq="D")
-        >>> idx.freqstr
-        'D'
-
-        The frequency can be inferred if there are more than 2 points:
-
-        >>> idx = pd.DatetimeIndex(
-        ...     ["2018-01-01", "2018-01-03", "2018-01-05"], freq="infer"
+        >>> datetimeindex = pd.date_range(
+        ...     "2022-02-22 02:22:22", periods=10, tz="America/Chicago", freq="h"
         ... )
-        >>> idx.freqstr
-        '2D'
-
-        For PeriodIndex:
-
-        >>> idx = pd.PeriodIndex(["2023-1", "2023-2", "2023-3"], freq="M")
-        >>> idx.freqstr
-        'M'
+        >>> datetimeindex
+        DatetimeIndex(['2022-02-22 02:22:22-06:00', '2022-02-22 03:22:22-06:00',
+                       '2022-02-22 04:22:22-06:00', '2022-02-22 05:22:22-06:00',
+                       '2022-02-22 06:22:22-06:00', '2022-02-22 07:22:22-06:00',
+                       '2022-02-22 08:22:22-06:00', '2022-02-22 09:22:22-06:00',
+                       '2022-02-22 10:22:22-06:00', '2022-02-22 11:22:22-06:00'],
+                      dtype='datetime64[ns, America/Chicago]', freq='h')
+        >>> datetimeindex.freq
+        <Hour>
         """
         return self._data.freq
 
@@ -669,21 +665,29 @@ def shift(self, periods: int = 1, freq=None) -> Self:
     @cache_readonly
     def inferred_freq(self) -> str | None:
         """
-        Tries to return a string representing a frequency generated by infer_freq.
-        Returns None if it can't autodetect the frequency.
+        Return the inferred frequency of the index.
+
+        Returns
+        -------
+        str or None
+            A string representing a frequency generated by ``infer_freq``.
+            Returns ``None`` if the frequency cannot be inferred.
 
         See Also
         --------
         DatetimeIndex.freqstr : Return the frequency object as a string if it's set,
-            otherwise None.
+            otherwise ``None``.
 
         Examples
         --------
-        For DatetimeIndex:
+        For ``DatetimeIndex``:
+
         >>> idx = pd.DatetimeIndex(["2018-01-01", "2018-01-03", "2018-01-05"])
         >>> idx.inferred_freq
         '2D'
-        For TimedeltaIndex:
+
+        For ``TimedeltaIndex``:
+
         >>> tdelta_idx = pd.to_timedelta(["0 days", "10 days", "20 days"])
         >>> tdelta_idx
         TimedeltaIndex(['0 days', '10 days', '20 days'],