@malikdiallo224
I like this series in pandas. thank you so much Corey.
@ahammadshawki8
Please make a playlist on numpy after pandas.
@corben3348
Good teaching is an art... This playlist is so helpful ! Thank you for your work !
@saravanannatarajan6515
Corey you're teaching is awesome!!! Much appreciated!!! Expecting series on Machine Learning/Deep Learning in the near future...
@gauravmarwaha8466
this series on pandas is the most complete and informative series ive found till date...!!!
@ishanpand3y
This is the most amazing series on Pandas ever. I just finished watching number 9th. Sir thank you so much providing such great content. 🧡🤍💚
@sayantanchakraborty75
Best series on Python Pandas . Thank you so much Mate. Love from India <3
@ashishdeora8522
Thank you Corey for this. My parents urged me to join your community. They are saying you are doing wonderful job. Thank you Corey for enabling us
@kuls43
11:36 we can use df.replace(['NA', 'Missing'], np.nan, inplace=True) instead
@benhancock1541
Thanks for this Corey - your tutorials are always great! I've been using pandas for almost 2 years and still learned stuff 👍
@adamgdev
You never disappoint!! And I never have to speed you up because you keep a great pace with no BS! Thank you!!
@srivathsgondi191
Now thats a lovely explaination, i like how u showed the function can be used in different scenarios!
@codegeek8256
Hi @ Corey Schafer I am very with your teachings, these are great building blocks towards data science, i hope one day we arrive there.
@njgaming4422
instead of replacing separately you can just pass the list of strings that you want replace E.g : df['YearsCode'].replace(['Less than 1 year','More than 50 years'],[0,51],inplace=True)
@gagansoni9665
i understand your pandas tutorials very clearly. this is helping me a lot. thank you so much corey. i wish to see your tutorials on machine learning using python.
@kirannagar8295
Hey , truly glad for your all series . If possible , please do make a course video on Pyspark .
@Al-Ahdal
Boss, it is requested to kindly make videos on comprehensive data analysis series, covering all aspects in much detail, and covering all possible areas for data analysis. Your channel and vdos are awesome. Great work indeed...... 👍
@alexthewebdesigner1856
@Corey Schafer Something told me that I'hd better watch this video. Just when I thought that I'd sanitized a large data set, I realize now that there could potentially be some data (or missing data) that could crash my application. Great video. Thank you Sir!
@ABDULKARIMHOMAIDI
Thanks man for such valuable series of videos, please add more video on new features on pandas !!!
@coreyms