When I'm writing the book (www.anotherbookondatascience.com) I always try to avoid the usage of tidyverse and got some criticism. But now I feel supported.
Yes, it is very brief. I tried to give some useful reference books/papers/links for each subject appeared in the book. Hope that is useful if the readers are willing to dive deeper. But the concept of linear programming itself is not complex, the users are generally not required to understand simplex/interior point algorithm. If they are able to translate the actual problem into the code then it is basically done. It is not like constrained optimization for which customized treatment based on mathematical theories is more important than writing the code.
`no beginner needs to learn how to write classes in R`.
a) using classes properly is great for all level R users;
b) a major reason that classes are not widely used (for beginners) is that S3/S4 are not easy to follow. R6 provides a natural and clear way to understand and write classes (especially for beginners).
Using classes at all is unnecessary for most R users. R is really, to the extent that paradigms matter to the average R user at all (which is: not much) a functional-first language. The idiomatic way to deal with the things you would use classes for is to use functions and closures. There are people who need objects in R, which is why R has object systems available, but it is of no help to a beginner to know them -- it doesn't help them to interact with the code they are going to see, and they don't have the background to understand why you would use classes instead of functions.
I have a similar feeling. And that is why I spent one whole chapter in data.table (and pandas). Hope more R users would like to learn and use data.table.
Thanks for adding the source for all the code snippets. I'd also be interested in the LaTeX (if that's what you used) source for the book itself if you feel like adding that.
