data_to_viz VS ggplot2-book

Maybe you refer to [1]? These are the two options I like to show students who first get in touch with data visualization.

[1] https://www.data-to-viz.com/

Here's a wonderful example: https://www.data-to-viz.com/

For plotting data, from Data to Viz is a great resource if you're comfortable (or willing to learn) using R or Python for data visualization. Even if you don't want to learn those, it's a great place to go for inspiration. https://www.data-to-viz.com/

Use data-to-viz https://www.data-to-viz.com/ for you data visualization needs. My guess is you’re looking for an UpSet plot.

also, the link I sent you has some code snippets for different kind or representations - https://www.data-to-viz.com/

If you want some suggestions for chart types, https://datavizcatalogue.com/search.html or https://www.data-to-viz.com/ might be helpful. You seem to need two types; a part-of-a-whole chart and a comparison chart. Some of your data is categorical, some is numerical. Those constraints should be sufficient to narrow down your choices.

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/