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 ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

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 ...

Traditionally, we analyzed data with our own eyes, but as our needs expanded, we developed tools to do the job for us. However, we currently deal with vast amounts of data that regular tools can’t ...

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 ...

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.

This article is adapted from an edition of our Off the Charts newsletter originally published in October 2021. Off the Charts is a weekly, subscriber-only guide to The Economist’s award-winning data ...