Retrieving from a multi-index in Pandas

What is a multi-index? How do I create one, and (more importantly), how do I retrieve from one? In this video, I show you a few techniques for working with multi-indexes, including the powerful "xs" method.
The Jupyter notebook for this (and all) videos are at github.com/reuven/KZbin-not.... And don't forget my free, weekly "Better developers" newsletter about Python and software engineering, at BetterDevelopersWeekly.com/.

[@CHeRKeSSS00]

OMG! OMG! OMG! What a content! I am speachless! After buying so many online courses I found you for free? OMG! OMG! OMG!

[@ReuvenLerner]

I'm so delighted you enjoyed it!

[@CHeRKeSSS00]

@@ReuvenLerner I was wondering if you teach on any other platforms? Anywhere to look at your courses? Thanks

[@ReuvenLerner]

@@CHeRKeSSS00 Yup, check out LernerPython.com -- lots of courses there!

[@horoshuhin]

your level of delivery of the material is one of the greatest I've seen. can't stress this enough. I'd prefer your videos over pandas documentation any day:). especially when describing edge cases, thanks

[@ReuvenLerner]

Thanks so much; I really appreciate it!

[@pietraderdetective8953]

Amazing..one of the most underrated Python/Pandas content creators. Awesome stuff Sir!

[@ReuvenLerner]

I'm so delighted you enjoy it!

[@TadeuszKurpiel]

Hi Reuven! for even more flexibility when selecting from multi-index data frames, you can use the 'get_level_values' method, for example like here: df[ df.index.get_level_values('Year').isin([1993, 1920, 2010]) & df.index.get_level_values('Sport').isin(['Archery', 'Judo']) & (df.Age < 24.0) ]

[@ReuvenLerner]

Excellent! I really like using xs, too.

[@osoriomatucurane9511]

Absolutely awesome

[@ReuvenLerner]

Glad to know you enjoyed it!

[@alanhernandez7201]

Hi Reuven! what happens if I have unique values, and I I want to know they qtys of each of them, how do I reshape in order to calculate that? by the way your Oreilly course was great!

[@ReuvenLerner]

Thanks so much, and great to see you here! I'm not 100% sure what you're asking here, but you can always group on a column and then use the "count" aggregate function to find out how many times each value appeared. If that's not what you meant, then let me know!

[@nguyenuchuy0330]

tNice tutorials doesn't seem to work.

[@ReuvenLerner]

What part didn't work for you? BTW, you can get the Jupyter notebook I used from GitHub, if that'll help.