Grouping Over All Possible Combinations of Several Variables With dplyr

Question

Given a situation such as the following

library(dplyr)
myData <- tbl_df(data.frame( var1 = rnorm(100), 
                             var2 = letters[1:3] %         


        

Answer 1

Using unite to create a new column is the simplest way

library(tidyverse)
df = tibble(
  a = c(1,1,2,2,1,1,2,2),
  b = c(3,4,3,4,3,4,3,4),
  val = c(1,2,3,4,5,6,7,8)
)
print(df)#output1
df_2 = unite(df, 'combined_header', a, b, sep='_', remove=FALSE) #remove=F doesn't remove existing columns
print(df_2)#output2

df_2 %>% group_by(combined_header) %>%
  summarize(avg_val=mean(val)) %>% print()#output3
#avg 1_3 = mean(1,5)=3 avg 1_4 = mean(2, 6) = 4

RESULTS

Output:
output1
 a     b   val
    
1     1     3     1
2     1     4     2
3     2     3     3
4     2     4     4
5     1     3     5
6     1     4     6
7     2     3     7
8     2     4     8

output2
  combined_header     a     b   val
               
1 1_3                 1     3     1
2 1_4                 1     4     2
3 2_3                 2     3     3
4 2_4                 2     4     4
5 1_3                 1     3     5
6 1_4                 1     4     6
7 2_3                 2     3     7
8 2_4                 2     4     8

output3
combined_header avg_val
               
1 1_3                   3
2 1_4                   4
3 2_3                   5
4 2_4                   6