Move example to docstring instead

Author: jahn96

doc/source/user_guide/categorical.rst

@@ -1185,12 +1185,4 @@ Counting CategoricalDtype
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
 As mentioned in :ref:`Equality Semantics <categorical.equalitysemantics>`, two instances of :class:`~pandas.api.types.CategoricalDtype` compare equal
-whenever they have the same categories and order. Therefore, when counting data types, the multiple instances of :class:`~pandas.api.types.CategoricalDtype` will be counted as one group if they have the same categories and order.
-In the example below, even though ``a``, ``c``, and ``d`` all have data types of ``category``, they will not be counted as one group since they don't have the same categories.
-
-.. ipython:: python
-
-    df = pd.DataFrame({'a': [1], 'b': ['2'], 'c': [3], 'd': [3]}).astype({'a': 'category', 'c': 'category', 'd': 'category'})
-    df
-    df.dtypes
-    df.dtypes.value_counts()
+whenever they have the same categories and order. Therefore, the multiple instances of :class:`~pandas.api.types.CategoricalDtype` will be counted as one group if they have the same categories and order.

pandas/core/base.py

@@ -1049,6 +1049,34 @@ def value_counts(
         4.0    1
         NaN    1
         Name: count, dtype: int64
+
+        **categorial_dtypes**
+
+        Rows with categorical type will be counted as one group\
+        if they have same categories and order.\
+        In the example below, even though ``a``, ``c``, and ``d``\
+        all have the same data types of ``category``,\
+        only ``c`` and ``d`` will be counted as one group\
+        since ``a`` doesn't have the same categories.
+
+        >>> df = pd.DataFrame({"a": [1], "b": ["2"], "c": [3], "d": [3]})
+                    .astype({'a': 'category', 'c': 'category', 'd': 'category'})
+        >>> df
+           a  b  c  d
+        0  1  2  3  3
+
+        >>> df.dtypes
+        a    category
+        b      object
+        c    category
+        d    category
+        dtype: object
+
+        >>> df.dtypes.value_counts()
+        category    2
+        category    1
+        object      1
+        Name: count, dtype: int64
         """
         return algorithms.value_counts_internal(
             self,