How do I select multiple rows and columns from a pandas DataFrame?

Have you ever been confused about the "right" way to select rows and columns from a DataFrame? pandas gives you an incredible number of options for doing so, but in this video, I'll outline the current best practices for row and column selection using the loc, iloc, and ix methods.

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[elpintor]

I love how he teaches, slow, thorough, easy to understand and with plenty of examples

[igorballesteros]

Your voice tone is perfect for learning. Great video!

[svin]

Congratulations on your marriage! Thanks for making awesome data school videos, I learned and refreshed lots of my Python skills here.

[RufusVidS]

I dropped into this video from another video and am so happy it happened! You have a very clear voice in the video, you clearly know your stuff, you give plenty of good examples of good practice and practices to avoid, and are quite thorough. I enjoyed this one very much and plan to check the others out right away. Also, congrats on your marriage, I hope you are still happily together now that a couple years have passed!

[AlexanderArtamonov]

After a few days of reading pandas documentation and numerous 'tutorials' I finally get a general principle of how loc/iloc works, thank you!

[prodigyswifeybaby]

Your pace is excellent! I like how you show the different options and recommendations. Keep up the good work!

[ahe]

Really great - though 4 years old video. Just learning Python and found u to be a great teacher. I will look for ur other videos Thanks

[mohamedel-gazzar]

legend absolute legend. I have been recently doing a course on data analysis and I keep coming back to this man's videos for help.

[TomSkinner]

Just wanted to pile on the accolades, thanks. Perfectly paced, clear, succinct. It was just what I needed.

[michellelee]

Just discovered this channel and I'm already eager to explore more! Thanks for breaking things down so simply and with tons of useful examples. I especially love it when you highlight to us efficient vs non-efficient / bug-prone codes.

[TheFallibleFiend]

I've watched this video several times and followed through with the exercise. But I just used iloc at work for the first time. Very handy.

[joro]

Well done! Thanks for going over the "proper" way first, and then the shortcuts. Most docs and tutorials, go straight to the shortcuts which is frusterating for a newb or even intermediate.

[chelseali]

Your explanations have been one the of best I have found so far on dataframes!

[urso]

Aside from the good video, your way of speaking makes the content easier to understand to non-English native speakers.

[vman]

Have watched this videos to refresh myself on two separate occasions. Very clear and concise with excellent examples. Thank you!

[TRNDSETR]

My brain is fried. I just watched 19 videos in 2 days and did every example also. But after watching I feel so much more confident. Im taking a class in a tech school currently, but your teaching is so much clearer. I learn more here, than in my class. My class is sooo fast, and long 5hr sessions at a time, its soo difficult to comprehend everything. Your videos are amazing. Thanks.

[goldensleeves]

This is GREAT. I'm in a software school right now and they did a MUCH WORSE job of explaining this. THANK YOU for this video. Thumbs up

[ManikandanRaju]

If had a million dollar with me, I would straight up come to you and give you the cash and learn from you. OMG!! You are a gem sir.

I am new to Python. I'm finding all your videos extremely useful. Beautifully explained, clear and concise. Slow and steady.

What else does one need!

Hats off!!!! Thank you so much.

[uh]

I have stuggled a bit with loc and iloc but after 12 min here everything just became clear. Thanks for an awesome explanation of this topic.

[genet]

I really like all your video tutorials.You explain things in a very methodological sequence with high clarity and gentle approach which is vital for beginner data science learners. We are very fortunate to have a free access to such high-quality educational resource. You are one of my favorite you-tube instructors I have ever watched.
Thank you one thousand times!!!