Computational Book on data/error analysis using R language?

[LCSphysicist]

Hello there.
Could you please recommend me a book that focus on data/error analysis and that, at the same time, provides examples of how to use the R programming language to such things?
It could be using the python or c++ languages instead.
The only books i have came across use fortran, but since i think it is becoming outdate to learn this language, i have decided to not use it.

 

[sysprog]

Maybe have a look at some web articles before buying a book, e.g.
https://data-flair.training/blogs/debugging-in-r-programming/

 

[sysprog]

Hello there.
Could you please recommend me a book that focus on data/error analysis and that, at the same time, provides examples of how to use the R programming language to such things?
It could be using the python or c++ languages instead.
The only books i have came across use fortran, but since i think it is becoming outdate to learn this language, i have decided to not use it.

In my opinion (and I'm in good company regarding this), Fortran, now about 65 years old, is by no means outdated $-$ it's an understatement to say that it has a very rich set of libraries $-$ many scientists and engineers find it indispensable for their work.

 

[CJ2116]

My two favorites that I use regularly (the first of which I actually learned R from) are:

R For Data Science, this goes through everything from importing, cleaning, visualizing and modeling (although this is the weakest section of the book). A slight word of warning with this, though; they use the 'Tidyverse' syntax, which is pretty different from base R syntax. This can be jarring and frustrating when you're trying to debug errors!

An Introduction to Statistical Learning, this is a much more mathematically advanced book (although very well written) that goes into modelling and error analysis. I do some statistical modelling for my job and reference this constantly, particularly the lab sections which work through a full project. This does use base R language.

 

[Office_Shredder]

Python is probably more generally useful to know if you are indifferent between languages for doing data science.