DOC: update the pandas.Series.dt.is_year_end docstring (#20274)

Author: janelle

pandas/core/indexes/datetimes.py

@@ -1790,7 +1790,7 @@ def freq(self, value):
         See Also
         --------
         quarter : Return the quarter of the date.
-        is_quarter_end : Similar method for indicating the start of a quarter.
+        is_quarter_end : Similar property for indicating the start of a quarter.
 
         Examples
         --------
@@ -1831,7 +1831,7 @@ def freq(self, value):
         See Also
         --------
         quarter : Return the quarter of the date.
-        is_quarter_start : Similar method indicating the quarter start.
+        is_quarter_start : Similar property indicating the quarter start.
 
         Examples
         --------
@@ -1871,7 +1871,7 @@ def freq(self, value):
 
         See Also
         --------
-        is_year_end : Similar method indicating the last day of the year.
+        is_year_end : Similar property indicating the last day of the year.
 
         Examples
         --------
@@ -1902,7 +1902,46 @@ def freq(self, value):
     is_year_end = _field_accessor(
         'is_year_end',
         'is_year_end',
-        "Logical indicating if last day of year (defined by frequency)")
+        """
+        Indicate whether the date is the last day of the year.
+
+        Returns
+        -------
+        Series or DatetimeIndex
+            The same type as the original data with boolean values. Series will
+            have the same name and index. DatetimeIndex will have the same
+            name.
+
+        See Also
+        --------
+        is_year_start : Similar property indicating the start of the year.
+
+        Examples
+        --------
+        This method is available on Series with datetime values under
+        the ``.dt`` accessor, and directly on DatetimeIndex.
+
+        >>> dates = pd.Series(pd.date_range("2017-12-30", periods=3))
+        >>> dates
+        0   2017-12-30
+        1   2017-12-31
+        2   2018-01-01
+        dtype: datetime64[ns]
+
+        >>> dates.dt.is_year_end
+        0    False
+        1     True
+        2    False
+        dtype: bool
+
+        >>> idx = pd.date_range("2017-12-30", periods=3)
+        >>> idx
+        DatetimeIndex(['2017-12-30', '2017-12-31', '2018-01-01'],
+                      dtype='datetime64[ns]', freq='D')
+
+        >>> idx.is_year_end
+        array([False,  True, False])
+        """)
     is_leap_year = _field_accessor(
         'is_leap_year',
         'is_leap_year',