diff --git a/6-NLP/4-Hotel-Reviews-1/README.md b/6-NLP/4-Hotel-Reviews-1/README.md
index fc7b916f30..e1d4d7f0ca 100644
--- a/6-NLP/4-Hotel-Reviews-1/README.md
+++ b/6-NLP/4-Hotel-Reviews-1/README.md
@@ -292,14 +292,14 @@ Here are the questions on their own, followed by the code and explanations:
    hotel_freq_df = hotel_freq_df.drop_duplicates(subset = ["Hotel_Name"])
    display(hotel_freq_df)
    
-   Hotel_Name									Total_Number_of_Reviews		Total_Reviews_Found
-   Britannia International Hotel Canary Wharf	9086						4789
-   Park Plaza Westminster Bridge London		12158						4169
-   Copthorne Tara Hotel London Kensington		7105						3578
+   Hotel_Name Total_Number_of_Reviews Total_Reviews_Found
+   Britannia International Hotel Canary Wharf 9086 4789
+   Park Plaza Westminster Bridge London 12158 4169
+   Copthorne Tara Hotel London Kensington 7105 3578
    ...
-   Mercure Paris Porte d Orleans				110							10
-   Hotel Wagner								135							10
-   Hotel Gallitzinberg							173							8
+   Mercure Paris Porte d Orleans 110 10
+   Hotel Wagner 135 10
+   Hotel Gallitzinberg 173 8
    ```
 
    You may notice that the *counted in the dataset* results do not match the value in `Total_Number_of_Reviews`. It is unclear if this value in the dataset represented the total number of reviews the hotel had, but not all were scraped, or some other calculation. `Total_Number_of_Reviews` is not used in the model because of this unclarity.