DOC: clarify that check_array_indexer accepts int and slice

- Updated parameter documentation to explicitly mention int, slice,
  and other non-array indexers are accepted
- Added examples showing int and slice usage
- Fixes #62562

Author: sah0725

pandas/core/indexers/utils.py

@@ -434,10 +434,11 @@ def check_array_indexer(array: AnyArrayLike, indexer: Any) -> Any:
     ----------
     array : array-like
         The array that is being indexed (only used for the length).
-    indexer : array-like or list-like
-        The array-like that's used to index. List-like input that is not yet
-        a numpy array or an ExtensionArray is converted to one. Other input
-        types are passed through as is.
+    indexer : array-like, list-like, int, slice, or other indexer
+        The indexer used for indexing. Array-like and list-like inputs that 
+        are not yet a numpy array or an ExtensionArray are converted to one. 
+        Non-array indexers (int, slice, Ellipsis, tuples, etc.) are passed 
+        through as is.
 
     Returns
     -------
@@ -486,6 +487,13 @@ def check_array_indexer(array: AnyArrayLike, indexer: Any) -> Any:
     >>> pd.api.indexers.check_array_indexer(arr, mask)
     array([ True, False])
 
+    Integer and slice indexers are passed through as is:
+
+    >>> pd.api.indexers.check_array_indexer(arr, 1)
+    1
+    >>> pd.api.indexers.check_array_indexer(arr, slice(0, 1, 1))
+    slice(0, 1, None)
+
     Similarly for integer indexers, an integer ndarray is returned when it is
     a valid indexer, otherwise an error is  (for integer indexers, a matching
     length is not required):