# How to Do an Inner Join in R (With Examples)

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```

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 <- merge(df1, df2, by='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.

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)

df3 <- inner_join(df1, df2, by='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.