Update

Author: AnonToky

pandas/core/indexes/datetimelike.py

@@ -89,7 +89,7 @@ class DatetimeIndexOpsMixin(NDArrayBackedExtensionIndex, ABC):
     _data: DatetimeArray | TimedeltaArray | PeriodArray
 
     def mean(self, *, skipna: bool = True, axis: int | None = 0):
-        """
+       """
         Return the mean value of the Array.
 
         Parameters
@@ -103,9 +103,25 @@ def mean(self, *, skipna: bool = True, axis: int | None = 0):
         -------
         scalar
             Timestamp or Timedelta.
+
+        See Also
+        --------
+        DatetimeIndex.median : Return the median of the index.
+        DatetimeIndex.sum : Sum of the values in the index.
+        DatetimeIndex.inferred_freq : Attempt to infer frequency from values.
+
+        Examples
+        --------
+        >>> import pandas as pd
+        >>> idx = pd.date_range("2020-01-01", periods=3)
+        >>> idx
+        DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03'],
+                      dtype='datetime64[ns]', freq='D')
+        >>> idx.mean()
+        Timestamp('2020-01-02 00:00:00')
         """
         return self._data.mean(skipna=skipna, axis=axis)
-
+        
     @property
     def freq(self) -> BaseOffset | None:
         """
@@ -149,6 +165,24 @@ def asi8(self) -> npt.NDArray[np.int64]:
     def freqstr(self) -> str:
         """
         Return the frequency string if it is set, otherwise None.
+
+        Returns
+        -------
+        str or None
+            Frequency string such as 'D', 'H', etc., or None.
+
+        See Also
+        --------
+        DatetimeIndex.freq : The offset object for the frequency.
+        PeriodIndex.freq : Return the frequency object for PeriodIndex.
+        DatetimeIndex.inferred_freq : Attempt to infer frequency from values.
+
+        Examples
+        --------
+        >>> import pandas as pd
+        >>> idx = pd.date_range("2020-01-01", periods=3, freq="D")
+        >>> idx.freqstr
+        'D'
         """
         from pandas import PeriodIndex
 
@@ -583,14 +617,28 @@ def shift(self, periods: int = 1, freq=None) -> Self:
         )
         return type(self)._simple_new(result, name=self.name)
 
-    @cache_readonly
+     @cache_readonly
     def inferred_freq(self) -> str | None:
         """
         Tries to return a string representing a frequency guess generated by infer_freq.
 
         Returns
         -------
         str or None
+            Inferred frequency string (e.g. 'D', 'H') or None if it cannot be inferred.
+
+        See Also
+        --------
+        DatetimeIndex.freqstr : Readable frequency string.
+        DatetimeIndex.freq : The offset object for the frequency.
+        pandas.infer_freq : Lower-level frequency inference utility.
+
+        Examples
+        --------
+        >>> import pandas as pd
+        >>> idx = pd.to_datetime(['2020-01-01', '2020-01-02', '2020-01-03'])
+        >>> idx.inferred_freq
+        'D'
         """
         return self._data.inferred_freq