I\'m writing functions that take in a data.frame
and then do some operations. I need to add and subtract items from the group_by
criteria in order to g
Here's an approach that uses tidyeval so that bare column names can be used as the function arguments. I'm not sure if it makes sense to convert the bare column names to text (as I've done below) or if there's a more elegant way to work directly with the bare column names.
drop_groups = function(data, ...) {
groups = map_chr(groups(data), rlang::quo_text)
drop = map_chr(quos(...), rlang::quo_text)
if(any(!drop %in% groups)) {
warning(paste("Input data frame is not grouped by the following groups:",
paste(drop[!drop %in% groups], collapse=", ")))
}
data %>% group_by_at(setdiff(groups, drop))
}
d = mtcars %>% group_by(cyl, vs, am)
groups(d %>% drop_groups(vs, cyl))
[[1]] am
groups(d %>% drop_groups(a, vs, b, c))
[[1]] cyl [[2]] am Warning message: In drop_groups(., a, vs, b, c) : Input data frame is not grouped by the following groups: a, b, c
UPDATE: The approach below works directly with quosured column names, without converting them to strings. I'm not sure which approach is "preferred" in the tidyeval paradigm, or whether there is yet another, more desirable method.
drop_groups2 = function(data, ...) {
groups = map(groups(data), quo)
drop = quos(...)
if(any(!drop %in% groups)) {
warning(paste("Input data frame is not grouped by the following groups:",
paste(drop[!drop %in% groups], collapse=", ")))
}
data %>% group_by(!!!setdiff(groups, drop))
}