Python for Data Analysis: Exploring and Cleaning Data 

I think your instruction is going to take my Python skills to another level. The pace was too fast initially but this is exactly what I need to watch after getting a basic understanding of object oriented programming.

Best and most complete Python for statistics course I found in RU-vid! Thank you!

Thank you Sir for all these videos on Python. Just started using Python after learning R. Your videos are very helpful. Keep on posting more videos on Python Data Analysis.

what I like the most is the provision of the code at your account in Kaggle, and the provision of the data sets. thank you

boss thank you so much. Going through this whole series in order. Thank you for making these.

It took me about 72 hours to find this useful chennel talking about python. Can't just thank you enough!!!!

Loving this! I'll have to rewatch this one to get everything. I'm practicing with mta turnstile data on my end

Awesome tutorial on data exploration, thank you, Sir. I specifically found valuable the trick to isolate the categorical data type objects and get the overview/summary.

Another great video, I sometimes paused it to try out bits of code in my own notebook. Thank you.

thank you for your really really perfect and step by step training. your video was very helpful for me,

Thanks so much for your video. This must be an extra tutorial out of my Data analytics paper. Really appreciate.

This kinda video is really helpful for newbies to the data analytics. Learning is by doing. And this is a very detailed example of doing it. Thanks for the great video!

Thank you sir, your videos are very helpful, simple and easy to understand.. thank you

Thank you for this video. Really insightful, and I can tell how experienced you are since you ask a lot of the right questions when starting a data analysis project!

Thank you for adding these very useful videos. They really add alot sepcially to beginners.

Thank you for your knowledge sharing. Very nice explanation with samples for each steps.

Replacing the nan values for the age variable with the artimethic mean. I am thinking loud, there is an alternative. Grouping the age into categories, then find the weighted mean (with the frequencies as weights) and fill the nan with the weighted mean.

it is better when you have homeworks , but i love this series.

Very useful!

sir what you taught in this lecture, my teacher took 12 hours and 2 weeks..... Thank you

Thank you!

Well explained.

Informative!

sir, i am doing this on google colab, my college told me to and some of your code from kaggle, like np.array, are not working on google colab, i removed it then it works fine and my teacher uses ' ' and you use " " and it doesnt effect the code yet what should i prefer, so as to master many diifrent coding languages

Hello sir, thank you so much for the tutorial. I'm actually stuck since my source in a CSV file. Except that sadly the file I'm working is extremely complex with indefinete columns since my main columns are repeated everyday based on the date. I've been stuck on this problem since over a week. Is there a way I could reach out to you and have your mail to maybe help solve this problem? Thanks a lot in advance.

bro used the darkest dataset available😂

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