All the functions in
dplyr (and many of the packages in the “hadleyverse”) use Non Standard Evaluation (NSE). NSE is extremely handy and generally reduces the amount of typing required. However functions that use NSE aren’t always intuitive to use. I mostly run into this issue when using
dplyr in a Shiny applications. Most recently I’ve run into this issue attempting to dynamically filter a
data.frame on different columns. This gist has a sample of the data I’m working with.
In base R filtering a
data.frame is fairly straight forward. However a fairly intuitive attempt to use
dplyr::filter doesn’t work, instead returning an empty
In order to evaluate this expression use the
lazyeval::interp function with
In the Shiny application I have a drop down input and text input to filter a
data.frame. The drop down input chooses the column to filter and the text input is the criteria for the filter. I haven’t been able to get this Standard Evaluation version to work with a database backend. The
dplyr vignette mentions NSE is important for database backends.
dplyr::*_ functions are Standard Evaluation equivalents, I’m not certain they’ll work for databases.