There are two common ways to perform an inner join in R:
Method 1: Use Base R
merge(df1, df2, by='column_to_join_on')
Method 2: Use dplyr
library(dplyr) inner_join(df1, df2, by='column_to_join_on')
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', 'G', 'H'), assists=c(4, 9, 14, 13, 10, 8)) df2 team assists 1 A 4 2 B 9 3 C 14 4 D 13 5 G 10 6 H 8
Example 1: Inner Join Using Base R
We can use the merge() function in base R to perform an inner join, using the ‘team’ column as the column to join on:
#perform inner join using base R 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 G 20 10 6 H 28 8
Notice that only the teams that were in both datasets are kept in the final dataset.
Example 2: Inner Join Using dplyr
We can use the inner_join() function from the dplyr package to perform an inner join, using the ‘team’ column as the column to join on:
library(dplyr) #perform inner 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 G 20 10 6 H 28 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 Add a Column to Data Frame in R
How to Drop Columns from Data Frame in R