There are two slightly different ways to do this depending on whether the function you’re working with is a “data-masking” function or a “tidy-selection” function.ĭf ] > input $ min, ] #> x y input #> 1 1 2 3 With these new terms we can make the problem of indirection more clear: we have a data-variable ( carat) stored inside an env-variable ( input$var), and we need some way to tell dplyr this. It’s going to be easier to understand what’s happening if we can disambiguate the two uses by introducing two new terms:Īn env-variable (environment variable) is a “programming” variables that you create with <-.Ī data-variable (data frame variables) is “statistical” variable that lives inside a data frame. That sentence might have made intuitive sense to you, but it’s a bit confusing because I’m using “variable” to mean two slightly different things. This is a problem of indirection: normally when using tidyverse functions you type the name of the variable directly in the function call.īut now you want to refer to it indirectly: the variable ( carat) is stored inside another variable ( input$var). The goal of the chapter is to help you understand why this doesn’t work, and why dplyr thinks you have asked for filter(diamonds, 'carat' > 1). Figure 12.1: An app that tries to select rows that are greater than a threshold on a user-selected variable.Īs you can see from Figure 12.1, the app runs without error, but it doesn’t return the correct result - all the rows have values of carat less than 1.

Solve any problem with indirection