DOC: Replace @appender with inline docstring for DataFrame.items

- Removed @appender decorator from DataFrame.items() method
- Inlined the complete docstring directly into the method
- Addresses issue #62437 to improve docstring clarity and standardization

Author: G26karthik

pandas/core/frame.py

@@ -1472,8 +1472,54 @@ def style(self) -> Styler:
         Name: population, dtype: int64
         """
 
-    @Appender(_shared_docs["items"])
     def items(self) -> Iterable[tuple[Hashable, Series]]:
+        """
+        Iterate over (column name, Series) pairs.
+
+        Iterates over the DataFrame columns, returning a tuple with
+        the column name and the content as a Series.
+
+        Yields
+        ------
+        label : object
+            The column names for the DataFrame being iterated over.
+        content : Series
+            The column entries belonging to each label, as a Series.
+
+        See Also
+        --------
+        DataFrame.iterrows : Iterate over DataFrame rows as
+            (index, Series) pairs.
+        DataFrame.itertuples : Iterate over DataFrame rows as namedtuples
+            of the values.
+
+        Examples
+        --------
+        >>> df = pd.DataFrame({'species': ['bear', 'bear', 'marsupial'],
+        ...                   'population': [1864, 22000, 80000]},
+        ...                   index=['panda', 'polar', 'koala'])
+        >>> df
+                species   population
+        panda   bear      1864
+        polar   bear      22000
+        koala   marsupial 80000
+        >>> for label, content in df.items():
+        ...     print(f'label: {label}')
+        ...     print(f'content: {content}', sep='\n')
+        ...
+        label: species
+        content:
+        panda         bear
+        polar         bear
+        koala    marsupial
+        Name: species, dtype: object
+        label: population
+        content:
+        panda     1864
+        polar    22000
+        koala    80000
+        Name: population, dtype: int64
+        """
         for i, k in enumerate(self.columns):
             yield k, self._ixs(i, axis=1)