This is a companion discussion topic for the original entry at:
Tidy evaluation is a new framework for non-standard evaluation that will be used throughout tidyverse. In this talk, I’ll introduce you to the problem that tidy eval solves, illustrated with examples of the various approaches used in R. I’ll then explain the most important components so that you can start writing your own functions instead of copying and pasting tidyr and dplyr code. I’ll finish with a small shiny app that shows how tidy eval is a natural fit for handling user input.
Hadley Wickham - Chief Scientist, RStudio, @hadley
Hadley is Chief Scientist at RStudio, a member of the R Foundation, and Adjunct Professor at Stanford University and the University of Auckland. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (the tidyverse: including ggplot2, dplyr, tidyr, purrr, and readr) and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and speaker promoting the use of R for data science. Learn more on his website, http://hadley.nz.