Відео

Your videos are really helpful. Please make this kind of project video with pyspark also. Thank you.

OMG keith you are a lifesaver! thank you!

Thanks Keith for this video! I'm new on data science I'm using your videos to practice and learn a lot more. Really thanks!

Thank you for the great overview of NLP!

It is still very helpful... straight to the point, many thanks

49 seconds theres a disgusting sound!

I just enter data analysis area and amazing this videos made 4 years before already! thanks for made this, learnt your skills and problem solving as talents, appreciated!

Man, you're crazy 🤣🤣🤣🤣🤣🤣🤣🤣🤣. This is awesome! Thanks for a colossal and great video!!!🎉🎉

Just a quick question...can i submitt this as my intro to Data science course semester project????

Great content, solution of 23 I believe is wrong.

My fiance is acrewed!

Thank you for this :)

The A.R.B Strongest Games Programs in the World! :) ua-cam.com/video/Xg36QswuC_U/v-deo.html

Thank you for this Keith .

Thank you such much!! whatever you are doing actually is life changing for people like me who is self learning these! Thank you!!!

in the last example you could bin the prices into bins of less than 5, 5-20, 20-50, 50-100, etc and use hue

On the final steps I get the error - agg function failed (using groupby). What might it be?

sir could u make same like numpy video

What I see is you should increase your testosterones replace running with building muscles.

More machine learning content! This is awesome stuff Keith!

Man, I have a comment here, to execute what you're doing in the part of groupby, it was necessary to do this: numeric_columns = df.select_dtypes(include='number') result = numeric_columns.groupby(df['Type 1']).mean() result The TypeError indicate that was not longer available the type of operations that you were doing in the video, hope this helps anyone!

Bro, you are a genius!!!

!ls is not recognized as an internal or external command, operable program or batch file. I'm using Anaconda in Windows 10. How to solve this problem, please help.

Hi Keith, can you check this out and pin @_Nelyen 's comment. Instead of writing: df.groupby(["Type 1"]).mean() Try writing: df.groupby(["Type 1"]).mean(numeric_only=True)

Fleet Battle - my id is Miaaaow... Fleet me betchez!!!

a couple of years ago (5 years) i did a pokemon pandas tutorial from you and it totally got me into the world of data science. i came back to say thanks for that tutorial. It really helped me. now am a python instructor.

Thank you so much brilliant guy, answered so many important questions 🙏

Your smile is and body language made me laugh... So hard .. you're a born comedian, thank you for such a great content man 😘

Hahahahahaha hahahahahaha hahahahahaha hahahahahaha hahahahahaha hahahahahaha hahahahahaha 😂😂😂 you're so funny... Don't know why I laugh a lot everytime I watch you.. thanks for making boring information so enjoyable

thanks a lot bro so good please make more

Thank you for this. I recently graduated with a masters in data science and finding a job has been brutal. Thank you for the tips.

Thailand bar girls here I come

Excellent! Thank you very much for this video!! Please more with this format 👏

Excellent tutorial to learn the fundamentals of SCI-Kit

Really amazing video! Thanks for the great content! For the part where it was allowing you to not escape the period in the square brackets, it's not sublime, you don't need to escape characters inside square brackets, although it won't complain if you do escape them. The only exception I can currently think of is the ^ symbol and only if you put it at the beginning.

29:26 - he starts writing some code

24:27 We can use gropyby to count the animals in the following way... df.groupby('animal')['animal'].count()

Are check and cheque meant to be similar?

This is the most practical Python tutorial video I've ever watched. Thanks for sharing!

Looking forward to numpy puzzles now!!

Loved the video, inspired to try, but no matter what I do I cannot get files to upload.

Thank you for sharing this! I hope you are feeling better these days!

What do you think is a good method to concatanate a string value from datafram column to anothee dataframe column by index key. Example, df_1 rows 10, 20, 26, 30, 40 column 5 (string) concatonate to df_2 rows 9, 19, 25, 29, 39 column 1?..

Such a great tutorial Keith. Please keep uploading such high quality videos on Pandas and many more

i would give this guy a 10/10...truly understood everything

just a note, at 1:19:21 the format = "mixed" isn't really working for me, and it fills the date_born column with NaT values. So, I tried format = "%d %B %Y" and it works

06:24 when that burrito you eat fights back

感谢你的辛苦付出

Bruh I’m here cuz I was playing this girl im dating and she clapped me like 10 times in a row. 😅 it was annoying cuz she never gave any tips, she literally just laughed the whole time.. I was literally getting annoyed cuz obviously I suck and she is just having a blast laughing at my misery lol.. And she always went first and in the middle. 🙄

Thank you man