Working with names and expressions in your tidy eval code - Lionel Henry

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.

About the Author

Lionel Henry

Lionel is a software developer at RStudio. He studied political science and statistics, developed a passion for writing R packages, and now assists Hadley in creating a rich data analysis framework.

Follow on Twitter Visit Website More Content by Lionel Henry
Previous Video
Welcome and RStudio Vision - Tareef Kawaf
Welcome and RStudio Vision - Tareef Kawaf

Next Video
Why TensorFlow eager execution matters - Sigrid Keydana
Why TensorFlow eager execution matters - Sigrid Keydana

In current deep learning with Keras and TensorFlow, when you've mastered the basics and are ready to dive i...