@julian59028
This is amazing. As a newbie to R videos like these motivate me to learn more.
@Smile-bq7mq
Thank you so much! You just saved my butt for a class project! And excellent job explaining everything! As for further analysis, it'd be cool to see a video on extracting common words in reviews. Or extract user sentiment from comments on a social media site.
@djangoworldwide7925
Why using xpath instead of css selector for classes? seems a bit tidius?
@tuhocr
This is amazing. Thank you!
@yearofthechris
Great video! Im having issues though, I am using a different link and have a different CSS element but same format. When I run the code I get some review dates but I also get other info like the city of the restaurant, and a photo count (i.e., [8]) Im kind of stumped as to why I am getting some other random info.
@chrishydock1897
Thank you -- this is super helpful. By chance, do you have the code posted anywhere?
@johng5295
Thanks in a million.
@djangoworldwide7925
can be interested to start a tf-idf using the ratings as documents, and get the most meaningful words per rating
@KianaAshoftehfard
This is amazing.I have a Q,why you didnt write all cods for i==0?
@kokabkhalid3181
Web scraping you are best
@KianaAshoftehfard
Thank you so much!How can i get this script?
@aminroshani
Thank you for your excellent video 👌👌 What we do if click on page numbers don't change the address?
@SamerHijjazi
You can find the updated tutorial here: https://youtu.be/UlBNf8g1wI8
@Raqi18
Great tutorial! Everything went well but Yelp suddenly banned my IP address. Any advice on how to remedy that? Also, for the ratings, the number of star ratings was more than the text and dates. So I couldn't really consolidate everything in the df framework. :(
@ahmadfraz5846
kindly share code repo
@ayaanshaikh8912
Can you do for LinkedIn too
@study-with-Albert