Update generic.py

pandas/core/groupby/generic.py

@@ -1613,7 +1613,8 @@ def value_counts(
         - If the groupby as_index is True then the returned Series will have a
           MultiIndex with one level per input column.
         - If the groupby as_index is False then the returned DataFrame will have an
-          additional column with the value_counts.
+          additional column with the value_counts. The column is labelled 'count' or
+          'proportion', depending on the ``normalize`` parameter.
 
         By default, rows that contain any NA values are omitted from
         the result.
@@ -1638,14 +1639,48 @@ def value_counts(
         4 	female 	high 	    FR
         5 	male 	low 	    FR
 
-        >>> df.groupby("gender").value_counts(normalize=True)
+        >>> df.groupby('gender').value_counts()
+        gender  education  country
+        female  high       FR         1
+                           US         1
+        male    low        FR         2
+                           US         1
+                medium     FR         1
+        dtype: float64
+
+        >>> df.groupby('gender').value_counts(ascending=True)
+        gender  education  country
+        female  high       FR         1
+                           US         1
+        male    low        US         1
+                medium     FR         1
+                low        FR         2
+        dtype: int64
+
+        >>> df.groupby('gender').value_counts(normalize=True)
         gender  education  country
         female  high       FR         0.50
                            US         0.50
         male    low        FR         0.50
                            US         0.25
                 medium     FR         0.25
         dtype: float64
+
+        >>> df.groupby('gender', as_index=False).value_counts()
+           gender education country  count
+        0  female      high      FR      1
+        1  female      high      US      1
+        2    male       low      FR      2
+        3    male       low      US      1
+        4    male    medium      FR      1
+
+        >>> df.groupby('gender', as_index=False).value_counts(normalize=True)
+           gender education country  proportion
+        0  female      high      FR        0.50
+        1  female      high      US        0.50
+        2    male       low      FR        0.50
+        3    male       low      US        0.25
+        4    male    medium      FR        0.25
         """
         if self.axis == 1:
             raise NotImplementedError(
@@ -1721,7 +1756,7 @@ def value_counts(
             if not self.as_index:
                 # Convert to frame
                 result = result.reset_index(name="proportion" if normalize else "count")
-            return result
+            return result.__finalize__(self.obj, method="value_counts")
 
 
 def _wrap_transform_general_frame(