diff --git a/piscine/week01/day01/ex01/README.md b/piscine/week01/day01/ex01/README.md
index 71f071b..30a52b9 100644
--- a/piscine/week01/day01/ex01/README.md
+++ b/piscine/week01/day01/ex01/README.md
@@ -2,20 +2,9 @@
 
 The goal of this exercise is to use many Python data types in **NumPy** arrays. **NumPy** arrays are intensively used in **NumPy** and **Pandas**. They are flexible and allow to use optimized **NumPy** underlying functions.
 
-1. Create a NumPy array that contains: an integer, a float, a string, a dictionary, a list, a tuple, a set and a boolean.
-
-The expected output is:
+1. Create a NumPy array that contains: an integer, a float, a string, a dictionary, a list, a tuple, a set and a boolean. Add the following code at the end of your python file or in a cell of the jupyter notebook: 
 
 ```python
 for i in your_np_array:
     print(type(i))
-
-<class 'int'>
-<class 'float'>
-<class 'str'>
-<class 'dict'>
-<class 'list'>
-<class 'tuple'>
-<class 'set'>
-<class 'bool'>
-```
\ No newline at end of file
+```