Delete group dplyr group_by

Question

In the case where Tibet is grouped by several variables in dplyr, is there a way to remove one grouping variable other than re-setting groups without this variable? I think it will be something like group_by(df, -var, add = TRUE), although it does not work.

Example:

library(dplyr)

# Works
mtcars %>%
  # Original groups
  group_by(cyl, gear, carb) %>%
  # New groups
  group_by(cyl, gear) %>%
  group_vars() 
# [1] "cyl"  "gear"

# Doesn't work
mtcars %>%
  # Original groups
  group_by(cyl, gear, carb) %>%
  # New groups
  group_by(-carb, add = TRUE) %>%
  group_vars() 
# [1] "cyl"   "gear"  "carb"  "-carb"

This is obviously a trivial example. In my actual use case, there are many conditional groupings based on user input, and I would just like to drop one group at some point in the function and leave the rest.

Answer 1

You can also use the .dotsspecification and group by all but a few. For instance.

library(dplyr)
ungroup_by <- function(x,...){
  group_by_(x, .dots = group_vars(x)[!group_vars(x) %in% ...])
}

mtcars %>%
  group_by(cyl, gear, carb) %>%
  ungroup_by('cyl') %>%
  group_vars() 
[1] "gear" "carb"

Similar information can be found on this post .

Answer 2

dplyr::groups dplyr::group_vars:

ungroup_some <- function(x,...){
  grps <- setdiff(group_vars(x),unlist(list(...)))
  group_by(x,.dots= grps)
}

mtcars %>%
  group_by(cyl, gear, carb) %>%
  ungroup_some("carb")

# # A tibble: 32 x 11
# # Groups:   cyl, gear [8]
#     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#  * <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#  1  21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
#  2  21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
#  3  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
#  4  21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
#  5  18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
#  6  18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1
#  7  14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
#  8  24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
#  9  22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
# 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
# # ... with 22 more rows