Hi, Good videos! Thanks. May you show some pro tips for example:? - Have 3 items in list - iterate over df in searching those 3 items in one column that keep in it - save rows that contain one of three item in column to new df
Great job. I just finished all this playlist and it helped me a lot. If you can help me if one question, how to print the information of rows that has the same value? ie. item index 1 has the height equals 180 and item index 5 has the same height, but the rest of the information are different. Basically, I want to group by a particular column. I try to find the answer everywhere, but I countn't.
watchin it 4 years later after u posted but still is the best tutorial videos from all of youtube , God bless u
Thanks for the work you put into this, brow!🙏 Can wait to start on the Machine Learning playlist!!
Pls continue
THANK YOU
Are you continuing with this?
2:05 I had changed some of the heights and characters off some TV show but the height he used for the last line ended up being the same :O
Hi, Good videos! Thanks. May you show some pro tips for example:?
- Have 3 items in list
- iterate over df in searching those 3 items in one column that keep in it
- save rows that contain one of three item in column to new df
Great job. I just finished all this playlist and it helped me a lot. If you can help me if one question, how to print the information of rows that has the same value? ie. item index 1 has the height equals 180 and item index 5 has the same height, but the rest of the information are different. Basically, I want to group by a particular column. I try to find the answer everywhere, but I countn't.
Like your video so muchhhh,really help me a lots!please keep this channel on,Thank you
Thanks
Thanks!!
Hey, I like your videos, keep up the good job! :D
For this video one question - what kind a plugin do you use for .csv files?
Muchas gracias bro, aprendí mas con esta serie que en la universidades, gracias crack
Thanks but why you don't use a dataset, this kind of small dataset you made is not in the real world.