Join us at rstudio::conf(2022) to sharpen your R skills. | July 25-28th in D.C.
Learn More
rstudio::conf(2022) | 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
RStudio Server
Shiny Server
R Packages
RStudio Academy
RStudio Cloud
RStudio Public Package Manager
shinyapps.io
RStudio Team
RStudio Workbench
RStudio Connect
RStudio Package Manager
rstudio::conf 2019 programming
Working with names and expressions in your tidy eval code
January 25, 2019
In practice there are two main flavors of tidy eval functions: functions that select columns, such as `dplyr::select()`, and functions that operate on columns, such as `dplyr::mutate()`. While sharing a common tidy eval foundation, these functions have distinct properties, good practices, and available tooling. In this talk, you'll learn your way around selecting and doing tidy eval style.
dplyr
:
:select
()
I work in the r-lib and tidyverse teams at RStudio. I’m interested in developing low-level tools that bring out the expressivity of the R language.