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Working with names and expressions in your tidy eval code

In practice there are two main flavors of tidy eval functions: functions that select columns, such as dplyr::sect(), and functions that operate on columns, such as dplyr::μtate().

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(),andfunctionstˆoperateoncolumns,suchasdplyr::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.

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About the speaker

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.