How can I write dplyr groups to separate files?

You can wrap the csv write process in a custom function as follows. Note that the function has to return a data.frame else it returns an error Error: Results are not data frames at positions

This will return 3 csv files named "mtcars_cyl_4.csv","mtcars_cyl_6.csv" and "mtcars_cyl_8.csv"

customFun  = function(DF) {
write.csv(DF,paste0("mtcars_cyl_",unique(DF$cyl),".csv"))
return(DF)
}

mtcars %>% 
group_by(cyl) %>% 
do(customFun(.))

The following works (you can skip the custom function)

library(dplyr)
library(readr)
group_by(mtcars, cyl) %>%
  do(write_csv(., paste0(unique(.$cyl), "test.csv")))

If you were willing to use data.table there is a slightly less clunky way of doing it.

require(data.table)
# Because this is a built in table we have to make a copy first
mtcars <- mtcars 
setDT(mtcars) # convert the data into a data.table

mtcars[, write.csv(.SD, paste0("mtcars_cyl_", .BY, ".csv")), by = cyl]

Note that the resulting table will not have a column for cyl (which would be redundant since it is stored in the file name, but maybe you want to leave it in for other reasons).

If you want cyl to be included in the output as a column you can use

mtcars[, write.csv(c(.BY,.SD), paste0("mtcars_cyl_", .BY, ".csv")), by=cyl]

With dplyr_0.8.0 this can be done with group_by_walk

library(dplyr)
library(readr)
mtcars %>%
   group_by(cyl) %>%
   group_walk(~ write_csv(.x, paste0(.y$cyl, "test.csv")))