There are two common ways to perform an outer join in R:
Method 1: Use Base R
merge(df1, df2, by='column_to_join_on', all=TRUE)
Method 2: Use dplyr
library(dplyr) full_join(df1, df2, by='column_to_join_on')
Each method will return all rows from both tables.
Both methods will produce the same result, but the dplyr method will tend to work faster on extremely large datasets.
The following examples show how to use each of these functions in practice with the following data frames:
#define first data frame df1 = data.frame(team=c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'), points=c(18, 22, 19, 14, 14, 11, 20, 28)) df1 team points 1 A 18 2 B 22 3 C 19 4 D 14 5 E 14 6 F 11 7 G 20 8 H 28 #define second data frame df2 = data.frame(team=c('A', 'B', 'C', 'D', 'L', 'M'), assists=c(4, 9, 14, 13, 10, 8)) df2 team assists 1 A 4 2 B 9 3 C 14 4 D 13 5 L 10 6 M 8
Example 1: Outer Join Using Base R
We can use the merge() function in base R to perform an outer join, using the ‘team’ column as the column to join on:
#perform outer join using base R df3 team', all=TRUE) #view result df3 team points assists 1 A 18 4 2 B 22 9 3 C 19 14 4 D 14 13 5 E 14 NA 6 F 11 NA 7 G 20 NA 8 H 28 NA 9 L NA 10 10 M NA 8
Notice that all of the rows from both data frames are returned.
Example 2: Outer Join Using dplyr
We can use the full_join() function from the dplyr package to perform an outer join, using the ‘team’ column as the column to join on:
library(dplyr) #perform outer join using dplyr df3 team') #view result df3 team points assists 1 A 18 4 2 B 22 9 3 C 19 14 4 D 14 13 5 E 14 NA 6 F 11 NA 7 G 20 NA 8 H 28 NA 9 L NA 10 10 M NA 8
Notice that this matches the result we obtained from using the merge() function in base R.
Additional Resources
The following tutorials explain how to perform other common operations in R:
How to Do a Left Join in R
How to Do a Right Join in R
How to Do an Inner Join in R