Excel vs. Python with Pandas - 5 Transformations You Need to Know | Python Tutorial

If you are a beginner or expert user with with excel or python, this tutorial will kickstart you towards being a data ninja. Here are the 5 key data transformations you need to know and I will show you how to do them both with excel and python using pandas

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[arquip]

Great video! I process all my data in excel, and know I am learning Python but I was not sure how to use it for data processing.

This gave me a better idea all the potential of python.

[Riddingwithvivian]

This is all great and great for me being an expert with excel but I realize I really need python. Basically as I see it when the dataset gets too big to house in excel you will need to house it somewhere else and that is when these "new" techniques come into play.

[mmazuma]

Stuff you share is CRAZY useful. Wonderful. Thanks for your efforts.

[WKB]

It is hard to read what you are typing in the notebook. Please zoom it closer in the next clip. Great clip, good idea to show it side by side excel vs python. thanks for this clip

[oscarmartinezbeltran]

Your Python tutorials are amazing!!!! Thanks!! Sugestion: "Power BI vs. Python" or "Power BI + Python"

[nitusidhu]

Awesome tutorial, thanks for putting things in perspective! Would love to see more videos related to this, such as handling common data analyst assignments when applying for jobs.

[maryannsalva]

Great tutorial! This is what I was looking for. Thank you.

[nonoobott]

Excellent video. You explained so well the comparison. Thanks for sharing

[wandag]

Great video, I learned so much. If I may offer one suggestion, please skip the background music on future videos, I found it a little bit distracting.

[KageanRage]

thank you very much for this video - exactly what I was looking for. I'm a big fan of excel, and even more so of python, so I'm fascinated to upskill in pandas.

[Ishkatan]

Nice job. Keeping up with the Excel instructions can be a challenge for someone not conversant with Excel. Please don't just shrug off details.

[Olly]

Great tutorial! I do think you're missing nearly 10 years of updates embedded in MS Excel that make things very easy to scale where speed is not a problem at all even when using data with millions of rows. Please look up power query/power pivot tools. You can literally do all this once and click and drag new csv's into a designated folder and have your entire analysis updated while your steps are documented. Furthermore things like data scraping, which I've done in both platforms, take a lot more effort (to me at least) in python. I guess it's knowing enough about each subject to adequately compare the two. I certainly need to learn more python and picked up a few things from your videos. However, in excel I'm a beast. Keep up the great work man!

[jingqingcheng]

Your tutorial is very useful and straighforward !! Many thanks !!

[sandrapaul]

How do we bring mean price and count price under a single column for each Bedroom. I mean, for Bedroom 1: mean, count ; Bedroom 2: mean, count

[MostafaHaliem]

Thank you for the tutorial, but you missed a very basic part, which is how did you get the data from Kaggle.

Appreciate if you can share the steps to get this data, this would allow us to test your code step by step on the same data you used on this tutorial.

Thank you in advance .

[MrWebon]

23:11 how do you jump from the column of sold to the equivalent column of mean in one keystroke?

[davidmitchell]

There is an error 'dfpiv=pd.pivot_table(df, index=['city'], values=['price', 'price'], columns=['bedrooms'], aggfunc=['count', 'mean'], fill_value=0)'. Not sure if it's due to the version of pandas i'm running. It works with values=['price'] (not twice) and and aggfunc = [np.count_nonzero, np.mean].

[jariuslouie]

Hi there! I can't get past the line of code that says:





I get this error:

ValueError: cannot convert float NaN to integer


Thank you very much Sir.

[mohamed.montaser]

nice video but in the barplot() u didn't specify the type of aggregation, how it figured out its average and not summed the values like what happened in excel

[khalilabdulnour]

when i df.describe(), the numbers are showing up with "e", such as what is causing this and how can i have it show normal format?