Advanced statistical modelling, hypothesis testing, and academic workflows make R preferred for data-heavy research and reproducible ...

R vs Python: What are the main differences? Your email has been sent More people will find their way to Python for data science workloads, but there’s a case to for making R and Python complementary, ...

Why write SQL queries when you can get an LLM to write the code for you? Query NFL data using querychat, a new chatbot component that works with the Shiny web framework and is compatible with R and ...

Reticulate is a handy way to combine Python and R code. From the reticulate help page suggests that reticulate allows for: "Calling Python from R in a variety of ways including R Markdown, sourcing ...

The world’s most popular programming language is losing market share to more specialized languages such as R and Perl, Tiobe ...

Java can handle large workloads, and even if it hits limitations, peripheral JVM languages such as Scala and Kotlin can pick up the slack. But in the world of data science, Java isn't always the go-to ...

Statistical programming language R has climbed back up to 8th place in Tiobe's latest programming language popularity index, just behind JavaScript and up from 20th position last July. In May, when R ...

As I frequently travel in data science circles, I’m hearing more and more about a new kind of tech war: Python vs. R. I’ve lived through many tech wars in the past, e.g. Windows vs. Linux, iPhone vs.

One of my favorite taglines is “the best run businesses run SAP®.” It is clean. It creates a sense of elitism by association. And upon hearing this tagline, those using SAP for planning think, “I am ...