DOC: clarify Series.map behavior for categorical dtype (#62338)

Author: Talyahav17

pandas/core/arrays/categorical.py

@@ -1585,6 +1585,22 @@ def map(
 
         >>> cat.map({"a": "first", "b": "second"}, na_action=None)
         Index(['first', 'second', nan], dtype='str')
+
+        The mapping function is applied to categories, not to each value. It is
+        therefore only called once per unique category, and the result reused for
+        all occurrences:
+
+        >>> cat = pd.Categorical(["a", "a", "b"])
+        >>> calls = []
+        >>> def f(x):
+        ...     calls.append(x)
+        ...     return x.upper()
+        >>> result = cat.map(f)
+        >>> result
+        ['A', 'A', 'B']
+        Categories (2, str): ['A', 'B']
+        >>> calls
+        ['a', 'b']
         """
         assert callable(mapper) or is_dict_like(mapper)
 

pandas/core/series.py

@@ -4419,6 +4419,34 @@ def map(
         2            NaN
         3  I am a rabbit
         dtype: object
+
+        For categorical data, the function is only applied to the categories:
+
+        >>> s = pd.Series(list("cabaa"))
+        >>> s.map(print)
+        c
+        a
+        b
+        a
+        a
+        0    None
+        1    None
+        2    None
+        3    None
+        4    None
+        dtype: object
+
+        >>> s_cat = s.astype("category")
+        >>> s_cat.map(print)  # function called once per unique category
+        a
+        b
+        c
+        0    None
+        1    None
+        2    None
+        3    None
+        4    None
+        dtype: object
         """
         if func is None:
             if "arg" in kwargs: