The easiest way to perform a cross join in R is to use the crossing() function from the package:

library(tidyr)

#perform cross join on df1 and df2
crossing(df1, df2)

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

Example: Perform Cross Join in R

Suppose we have the following two data frames in R:

#define first data frame
df1 = data.frame(team1=c('A', 'B', 'C', 'D'),
                 points=c(18, 22, 19, 14))

df1

  team1 points
1     A     18
2     B     22
3     C     19
4     D     14

#define second data frame
df2 = data.frame(team2=c('A', 'B', 'F'),
                 assists=c(4, 9, 8)) 

df2

  team2 assists
1     A       4
2     B       9
3     F       8

We can use the crossing() function from the tidyr package to perform a cross join on these two data frames:

library(tidyr)

#perform cross join 
cross <- crossing(df1, df2)

#view result
cross

# A tibble: 12 x 4
   team1 points team2 assists
         
 1 A         18 A           4
 2 A         18 B           9
 3 A         18 F           8
 4 B         22 A           4
 5 B         22 B           9
 6 B         22 F           8
 7 C         19 A           4
 8 C         19 B           9
 9 C         19 F           8
10 D         14 A           4
11 D         14 B           9
12 D         14 F           8

The result is a data frame that contains every possible combination of rows from each data frame.

For example, the first row of the first data frame contains team A and 18 points. This row is matched with every single row in the second data frame.

Next, the second row of the first data frame contains team B and 22 points. This row is also matched with every single row in the second data frame.

The end result is a data frame with 12 rows.

Additional Resources