Something not discussed much, R has a “license” issue.
Perhaps this is a topic which requires its own post, so you may skip this part. Currently no other language/system is close to R in this context as a whole. You can simply analyze your data and generate reports (word, pdf, powerpoint, dashboard etc.) for the relevant stakeholders. dplyr+ggplot2), Shiny and RMarkdown it is both an analytical powerhouse and a seamless communication tool. R is simply an amazing language created for (pardon my French) non-CS people. I also used to say that people who come from Excel find R (with tidyverse) better and those who come from Java find Python better. Especially those whose backgrounds do not include computer science (CS) or similar majors tend to pick up and use these languages instead of Java, C++ etc. It would not be entirely wrong if we say that three programming languages which data scientists use the most are Python, R and Julia. This will be a post about both R and Rstudio/Posit. This post is written by my perspective and my tooling needs from these languages. I will also still continue to teach R and develop in R. Needless to say, these are solely my opinions.
Alas, even though calling the demise of R is quite premature, it is definitely a sign for contemplation. Is it the end of R?😱 No, I don’t think so. I also noticed that, lately I use Python more than R, because I write production code for SaaS stuff and my fellow developers prefer Python for better integration. I also use develop with both R and Python (and occasional attempts on Julia. I teach R with data analysis and communication focus.
So, what does this change mean for R and other data science languages? As expected, they already showcased some major developments such as Shiny for Python and Quarto. Highlight of the announcement is to take further steps in Python (without giving up on R). RStudio’s latest announcement on changing its name to Posit definitely means a lot.
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