Python Pandas Tutorial (Part 6): Add/Remove Rows and Columns From DataFrames

In this video, we will be learning how to add and remove our rows and columns.

In this Python Programming video, we will be learning how to add and remove rows and columns from dataframes using the append and drop methods. We will also see how we can create new columns by combining elements from existing ones. Let's get started...

The code for this video can be found at:

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[coreyms]

Hey everyone. Hope you're all having a great weekend. I'm still working on finishing up the series. Let me know if there is anything specific you want me to cover. In the next video I'll be covering sorting, and some videos still to come include: working with dates, aggregating data, reading and writing to/from different sources, and a discussion on the recent Pandas version 1.0 release. Let me know if there is anything else you'd like to see! Thanks and have a good one!

[andynelson]

8:00 if you're getting a FutureWarning on append method, you can you concat method instead. df = pd.concat([df, pd.DataFrame.from_records([{ 'first': 'Tony'}])])

[suryatejasunny]

Thank you Brilliant for sponsoring Corey.

[ritikjawalkar]

For all those who are coding in 2023 .append function has been changed into ._append

[halim_Ha]

The happiness rises when you get notification from corey

[RAJASEKARCMR]

07:56 instead of ' append() ' -> ' _append() ' works (underscore in front)

[fahadshoaib]

Adding column 0:43
Removing column 3:08
Adding rows to data frame 6:40
Adding two data frames 9:45
Removing rows 12:11

[expat]

Aside from the unparalleled level of instruction, the production of these videos is superb. Only one of the 5 commercial courses I have taken was in the same league.

[dipayanroy]

Corey,

Can I request a tutorial series on date time forecasting through machine learning? I've gone various videos and articles, but none of them match your clarity and simple way of explaining complex things. Would really love to see that!

[elikent]

Hey Corey. Just wanted to say your videos are the best I've come across yet explaining how Pandas works. Great job. Thank you!

[Kralnor]

Thanks for this excellent video series on Pandas. Your style is much cleaner and easier to follow than by trying to read through the official docs and various Stackoverflow posts.
I'd really like to see a video on the different df.merge variations, particularly using MultiIndex and handling duplicates.

[babatundekelvinifeoluwa]

Great videos!
I can proudly, your tutorial are the best online tut on python I've ever come across so far...

[akritisstory]

Thank you Brilliant for sponsoring this course. Many people are getting help as more and more data analytics jobs are coming, this video is must.

[fhdhejeh]

I am sure that I will never forget about the sponsor of this video

[ciprianp]

Wow, man! With a little bit of help from Google and your videos, I was able to automate an Excel File ... Thank you and keep it going! You rock!

[ZsoltPal]

amazing, thank you for these! aside me banging my head into the table from the mix of syntax styles and asking out loud "how the heck will I remember all these" by where do you need 'inplace' and where not, when do you to pass what, the videos are a godsend!

[GuilhermeMendesG]

Corey, you saved my life! Thank you so much for this amazing series. I've learned so much!

[BugMagnet]

Thank you so much for these easy to understand tutorials. My guess is these will get millions of views once schools discover that programming should be a core subject.

[Tolgo_on_youtube]

Amazing content, thanks for making this complicated topic intelligible, accessible, and available.

[questscape]

The speed of information that flows in is insane. Amazing playlist 🙌