# R: How to Merge Data Frames Based on Multiple Columns

You can use the following basic syntax to merge two data frames in R based on multiple columns:

```merge(df1, df2, by.x=c('col1', 'col2'), by.y=c('col1', 'col2'))
```

The following example shows how to use this syntax in practice.

### Example: Merge Data Frames on Multiple Columns

Suppose we have the following two data frames in R:

```#define data frames
df1 = data.frame(playerID=c(1, 2, 3, 4, 5, 6),
team=c('A', 'B', 'B', 'B', 'C', 'C'),
points=c(19, 22, 25, 29, 34, 39))

df2 = data.frame(playerID=c(1, 2, 3, 4),
tm=c('A', 'B', 'B', 'B'),
rebounds=c(7, 8, 8, 14))

#view first data frame
df1

playerID team points
1        1    A     19
2        2    B     22
3        3    B     25
4        4    B     29
5        5    C     34
6        6    C     39

#view second data frame
df2

playerID tm rebounds
1        1  A        7
2        2  B        8
3        3  B        8
4        4  B       14```

Notice that the two data frames share the playerID column, but the team columns have different names in each data frame:

• The first data frame has column ‘team
• The second data frame has column ‘tm

In order to merge these data frames based on the playerID and the team columns, we need to use the by.x and by.y arguments.

We can use the following code to perform this merge:

```#merge two data frames
merged = merge(df1, df2, by.x=c('playerID', 'team'), by.y=c('playerID', 'tm'))

#view merged data frame
merged

playerID team points rebounds
1        1    A     19        7
2        2    B     22        8
3        3    B     25        8
4        4    B     29       14
```

The final merged data frame contains data for the four players that belong to both original data frames.