Join us at rstudio::conf(2022) to sharpen your R skills.
| July 25-28th in D.C.
July 25-28th in D.C.
7/25 - 7/28 in D.C.
The premier IDE for R
RStudio anywhere using a web browser
Put Shiny applications online
Shiny, R Markdown, Tidyverse and more
Next level training for you and your team
Do, share, teach and learn data science
An easy way to access R packages
Let us host your Shiny applications
A single home for R & Python Data Science Teams
Scale, develop, and collaborate across R & Python
Easily share your insights
Control and distribute packages
RStudio Public Package Manager
RStudio Package Manager
The Power of Great Datasets
January 21, 2021
There are a few classic datasets, like mtcars, nycflights, or Titanic passengers. They're okay, but they leave something to be desired for folks learning R: they're kind of boring.
There's a big difference between "Okay Datasets" and "Great Datasets". Great Datasets prompt you to exclaim, "That's so cool!" They get your blood pumping and mind racing with questions you want answered. They give tremendous motivation to answer those questions. And in answering those questions, you'll probably learn some R.
I want you to curate Great Datasets. You'll contribute to the richness of our community, you'll learn some R yourself, and you'll feel fantastic when someone finds your Great Dataset and exclaims, "That's so cool!"
Alex Cookson, Jeroen Ooms and Marie Vendettuoli Q&A
Alex Cookson helps the Customer Intelligence team at the Royal Canadian Mint make the most of their data. When he’s not working on A/B testing, recommendation engines, or exploratory data analysis at the Mint, he can be found participating in Tidy Tuesday or thinking up cool datasets to explore. And when he’s not doing that, he’s probably cycling around Toronto or doting on his two cats, Tom Tom and Ruby.