The idea is to patch a call to ggplot in a function.
The example:
library(dplyr)
library(ggplot2)
library(lazyeval)
df <- data.frame(A=letters[1:10], B=2:11, C=3:12))
func <- function(name, dat=df) {
output <- dat %>%
select_(~A,name) %>%
arrange_(interp(~desc(var), var=as.name(name)))
plot <-
ggplot(output, aes_string(x=reorder(~A,-name), y=B)) +
geom_bar(stat='identity')
print(plot)
return(plot)
}
result <- func("B")
Compiling gives:
Error in -name : invalid argument to unary operator.
I tried deparse
and substitute
. Not sure I got the right combo. Any ideas?
Reorder the data before passing it to ggplot
. The following code also moves some of the column names around in the ggplot
call, because otherwise you’d always be plotting A
against B
, regardless of the name
argument — or was that intentional?
function (dat, name) {
var = as.name(name)
reord = list(interp(~ reorder(var, -var), var = var))
output = dat %>%
select_(~A, name) %>% # Not actually necessary.
arrange_(interp(~ desc(var), var = var)) %>%
mutate_(.dots = setNames(reord, name))
plot = ggplot(output, aes_string(x = 'A', y = name)) +
geom_bar(stat = 'identity')
plot(plot)
plot
}
func(df, 'B')
I’m using the mutate_(.dots = …)
form here. Have a look at dplyr’s “NSE” vignette for more information on its usage.