diff --git a/2-Working-With-Data/07-python/README.md b/2-Working-With-Data/07-python/README.md
index 119b53cb9..4a2974a1e 100644
--- a/2-Working-With-Data/07-python/README.md
+++ b/2-Working-With-Data/07-python/README.md
@@ -173,7 +173,7 @@ df.iloc[:5]
 
 **Grouping** is often used to get a result similar to *pivot tables* in Excel. Suppose that we want to compute mean value of column `A` for each given number of `LenB`. Then we can group our DataFrame by `LenB`, and call `mean`:
 ```python
-df.groupby(by='LenB').mean()
+df.groupby(by='LenB').[['A','DivA']]mean()
 ```
 If we need to compute mean and the number of elements in the group, then we can use more complex `aggregate` function:
 ```python