diff --git a/docs/source/access.mdx b/docs/source/access.mdx
index f925056e0cf..ecdfbbf446b 100644
--- a/docs/source/access.mdx
+++ b/docs/source/access.mdx
@@ -57,12 +57,18 @@ You can combine row and column name indexing to return a specific value at a pos
 But it is important to remember that indexing order matters, especially when working with large audio and image datasets. Indexing by the column name returns all the values in the column first, then loads the value at that position. For large datasets, it may be slower to index by the column name first.
 
 ```py
->>> with Timer():
-...    dataset[0]['text']
+>>> import time
+
+>>> start_time = time.time()
+>>> text = dataset[0]["text"]
+>>> end_time = time.time()
+>>> print(f"Elapsed time: {end_time - start_time:.4f} seconds")
 Elapsed time: 0.0031 seconds
 
->>> with Timer():
-...   dataset["text"][0]
+>>> start_time = time.time()
+>>> text = dataset["text"][0]
+>>> end_time = time.time()
+>>> print(f"Elapsed time: {end_time - start_time:.4f} seconds")
 Elapsed time: 0.0094 seconds
 ```
 
@@ -143,4 +149,4 @@ But unlike [slicing](access/#slicing), [`IterableDataset.take`] creates a new [`
 
 Interested in learning more about the differences between these two types of datasets? Learn more about them in the [Differences between `Dataset` and `IterableDataset`](about_mapstyle_vs_iterable) conceptual guide.
 
-To get more hands-on with these datasets types, check out the [Process](process) guide to learn how to preprocess a [`Dataset`] or the [Stream](stream) guide to learn how to preprocess an [`IterableDataset`].
\ No newline at end of file
+To get more hands-on with these datasets types, check out the [Process](process) guide to learn how to preprocess a [`Dataset`] or the [Stream](stream) guide to learn how to preprocess an [`IterableDataset`].