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I love this cheat sheet, thanks for making it!

A small suggestion: I think the "Reshape Data - changing layout" section would be easier to understand with different colors for the different variables. I actually didn't understand the illustrations at first, then I read the pandas cheat sheet and immediately got it 😊

This style of documentation is very simple and perfect, Many people like it very much!!
Can you do the same style documentation for other well-known packages?? such as Flux, MLJ, DifferentialEquations ...

Thank you very much for your work, I love this cheat sheet !

Can i get the code of DataFramesCheatSheet_v1.x_rev1.pdf, I want to translate it into Chinese

I think that I found a typo in pub/data-wrangling-with-data-frames-jl-cheat-sheet.md. Under the section Where to get data, in the example code, it says function download_titantic(). I believe that it is meant to say function download_titanic(). It's a very subtle typo.

It would be great to release an updated version of the cheat sheet to DataFrames.jl 1.1.1. Thank you!

Hi,

Great resource this DataFrames.jl cheat sheet. However, I noticed a small error in the "Handling Missing Data" section. Under both allowmissing(df, :sibsp) and disallowmissing(df, :sibsp) is the same text "Change column to allow missing data." I take it that under disallowmissing(df, :sibsp) the text should actually be "Change column to disallow missing data."

But apart from that, thanks for taking the time to put this up! I've been hoping to get my hands on such a cheat sheet for quite a while now!

First off, this is awesome - I will definitely print one and put it on my wall 👍. I just have a couple of suggestions:

• I don't know what sibsp is. It's probably clear in the context of the titanic dataset, but things like sex class and fare all seem like good options, since they can probably be intuited even if a person isn't familar with the dataset. I can understand not wanting to reuse the same ones over and over, but if there are other options, I think it would be worth using them (or just explain sibsp better in the help text)
• under "Select observations" section, you might want to mention that you can use unique! to mutate to be consistent.
• same section - I often use unique!(df, [cols...]) syntax, which only checks certain columns for uniqueness. Might be worth adding.
• Not totally clear what that weird "R" symbol - indexing means. Is it just row-wise? Or related to R language?
• Also, that syntax can also be used to index columns at the same time - is that worth a note? (I realize space is limited)