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
Running the above still only shows the means of cyl and vs combined, and not individually — user1165199

Sotos Sotos · Accepted Answer · 2017-01-20T13:20:33

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

Summarise for multiple group_by variables combined and individually

1 Answers