Summarise for multiple group_by variables combined and individually

Question

I am using dplyr's group_by and summarise to get a mean by each group_by variable combined, but also want to get the mean by each group_by variable individually.

For example if I run

mtcars %>% 
  group_by(cyl, vs) %>% 
  summarise(new = mean(wt))

I get

    cyl    vs      new
  <dbl> <dbl>    <dbl>
     4     0 2.140000
     4     1 2.300300
     6     0 2.755000
     6     1 3.388750
     8     0 3.999214

But I want to get

    cyl    vs      new
  <dbl> <dbl>    <dbl>
     4     0 2.140000
     4     1 2.300300
     4    NA 2.285727
     6     0 2.755000
     6     1 3.388750
     6    NA 3.117143
     8     0 3.999214
    NA     0 3.688556
    NA     1 2.611286

I.e. get the mean for the variables both combined and individually

Edit Jaap marked this as duplicate and pointed me in the direction of Using aggregate to apply several functions on several variables in one call. I looked at jaap's answer there which referenced dplyr but I can't see how that answers my question? You say to use summarise_each, but I still don't see how I can use that to get the mean of each of my group by variables individually? Apologies if I am being stupid...

i think you should try this you have to factorize your grouping variables. mtcars %>% mutate(cyl=as.factor(cyl),vs=as.factor(vs)) %>% group_by(cyl,vs) %>% summarise(new=mean(wt)) — jarry jafery, Jan 20 '17 at 12:51
Running the above still only shows the means of `cyl` and `vs` combined, and not individually — user1165199, Jan 20 '17 at 13:14

score 1 · Accepted Answer · answered Jan 20 '17 at 13:20

Here is an idea using bind_rows,

library(dplyr)

mtcars %>% 
     group_by(cyl, vs) %>% 
     summarise(new = mean(wt)) %>% 
    bind_rows(., 
              mtcars %>% group_by(cyl) %>% summarise(new = mean(wt)) %>% mutate(vs = NA), 
              mtcars %>% group_by(vs) %>% summarise(new = mean(wt)) %>% mutate(cyl = NA)) %>% 
   arrange(cyl) %>% 
   ungroup()

# A tibble: 10 × 3
#     cyl    vs      new
#   <dbl> <dbl>    <dbl>
#1      4     0 2.140000
#2      4     1 2.300300
#3      4    NA 2.285727
#4      6     0 2.755000
#5      6     1 3.388750
#6      6    NA 3.117143
#7      8     0 3.999214
#8      8    NA 3.999214
#9     NA     0 3.688556
#10    NA     1 2.611286

Thanks, was hoping there'd me an argument in the group_by which allows you to do this, but with the lack of that I guess this is the quickest and easiest method — user1165199, Jan 20 '17 at 13:38

Summarise for multiple group_by variables combined and individually

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