[anjanb]

I'm a dataframes noob. I saw this post and the performance claims attracted me. I went to chatGPT to understand what dataframes were about. Then on udemy, I searched for a polar course. A course required pre-requisites : a bit about jupyter notebooks and pandas. Then I went through a few modules of a pandas course. Now, I'm going through a polars course. Altogether, I spent about 2-3 hours to setup the environment and know what this is all about.

A little bit context would have helped to have attracted a lot more noobs.g

[sanderjd]

Your first paragraph makes perfect sense! I was nodding along. But then your concluding sentence was a bit of a record scratch for me. This all worked as intended! You knew what the project was about - "data frames" - and what might make it attractive to you - the performance claims - and then you went and followed exactly the right path to get the context you needed to understand what's going on with it. It's a big topic that you were able to spin up on to a basic level in 2-3 hours, by pulling on strings starting at this landing page. This is a very successful outcome.

I'd also recommend this book: https://wesmckinney.com/book/. It's not about polars, but you'd be able to transfer its ideas to polars easily once you read it.

[_dain_]

"How To Be A Pandas Expert"[1] is a good primer on dataframes. There's a certain mental model you need to use dataframes effectively but it's not apparent from reading the official docs. The video makes it explicit: dataframes are about like-indexed one-dimensional data, and every dataframe operation can be understood in terms of what it does to the index.

[1] https://www.youtube.com/watch?v=oazUQPrs8nw