ggplot2-book VS r4ds

I also only recently started using ggplot after doing most of my graphs with base R‘s plot() function. I started by reading ggplot2 by Hadley Wickham which is also available as a free ebook. Reading the first few chapters is enough to enable you to plot many basic plots. I can’t imagine going back to any other visualization tool ever again. Absolutely love the freedom ggplot gives you.

His ggplot book will teach you all you need to know about R plotting, and is probably right at your current level. It is likewise pretty great, ggplot

The OG book is still the best in my opinion! https://ggplot2-book.org/

You could use base R, see ?plot but a lot of people would use ggplot2. However, looking at your data it won’t look very good because there’s going to be very few points per country.

If you included DESCRIPTION to your repository (like in ggplot2-book - https://github.com/hadley/ggplot2-book/blob/master/DESCRIPTION ) devtools::install_deps() and renv::install() will install dependencies listed there as would pip with requirements.txt , you can trigger this from your R script, from command line or from whatever deployment / automation tool you are using.

Chapters 1-8 of https://adv-r.hadley.nz/, https://r4ds.had.co.nz/ , and https://ggplot2-book.org/ were covered in my statistical computing courses. I don't think it gets much more advanced than that at the undergrad level.

You can check out more about Ggplot2 here: https://ggplot2-book.org/

* "ggplot2: Elegant graphics for data analysis" : https://ggplot2-book.org/

https://r4ds.hadley.nz is free and very good

R for Data Science teaches you the tidyverse packages, which makes data wrangling so much easier!

One of the best free resources is the R4DS book by Hadley Wickham. You should make sure you start with the in progress second edition. https://r4ds.hadley.nz/

The first edition of R4DS is quite old now. Check out the soon to be released second edition: https://r4ds.hadley.nz/

R for Data Science (2nd Ed), the updated guide from Hadley Wickham

The big skills gap you have is in practical data exploration and transformation, which will be a large part of any data-centric role. As much as people may have distaste for it, there is no avoiding data manipulation as critical foundational enabler of all inferential and predictive modeling work. SQL is the lingua franca here and well worth picking up the basics (joins, window functions, handling dates and times, etc.), plus learning how to implement similar transformations in R and Python. With appropriately transformed data, you then need to be able to visualize it effectively using tools like Tableau or ggplot2 in R. I would not necessarily seek courses or certificates in it but expect to be evaluated on them in technical interview screenings, so self-study accordingly. R for Data Science by Hadley Wickham is a great free resource for these topics for R.

I just looked and there is now a second edition! https://r4ds.hadley.nz/