How to Compare Three Columns in R (With Example)

You can use the following basic syntax to compare the values in three columns in R:

df$all_matching <- df$A == df$B & df$B == df$C

This syntax creates a new column called all_matching that returns a value of TRUE if all of the columns have matching values, otherwise it returns FALSE.

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

Example: Compare Three Columns in R

Suppose we have the following data frame in R with three columns:

#create data frame
df <- data.frame(A=c(4, 0, 3, 3, 6, 8, 7, 9, 12),
                 B=c(4, 2, 3, 5, 6, 4, 7, 7, 12),
                 C=c(4, 0, 3, 5, 5, 10, 7, 9, 12))

#view data frame
df

   A  B  C
1  4  4  4
2  0  2  0
3  3  3  3
4  3  5  5
5  6  6  5
6  8  4 10
7  7  7  7
8  9  7  9
9 12 12 12

We can use the following code to create a new column called all_matching that returns TRUE if all three columns match in a given row and FALSE if they do not:

#create new column that checks if values in all three columns match
df$all_matching <- df$A == df$B & df$B == df$C

#view updated data frame
df

   A  B  C all_matching
1  4  4  4         TRUE
2  0  2  0        FALSE
3  3  3  3         TRUE
4  3  5  5        FALSE
5  6  6  5        FALSE
6  8  4 10        FALSE
7  7  7  7         TRUE
8  9  7  9        FALSE
9 12 12 12         TRUE

The new column called all_matching shows whether or not the values in all three columns match in a given row.

For example:

All three values match in the first row, so TRUE is returned.
Not every value matches in the second row, so FALSE is returned.
All three values match in the third row, so TRUE is returned.

And so on.

If you would like to return values other than TRUE and FALSE, you can specify those values in an ifelse() function.

For example, we can use the following code to return ‘Yes’ if the values in all three columns match or ‘No’ otherwise:

#create new column that checks if values in all three columns match
df$all_matching <- ifelse(df$A == df$B & df$B == df$C, 'Yes', 'No')

#view updated data frame
df

   A  B  C all_matching
1  4  4  4          Yes
2  0  2  0           No
3  3  3  3          Yes
4  3  5  5           No
5  6  6  5           No
6  8  4 10           No
7  7  7  7          Yes
8  9  7  9           No
9 12 12 12          Yes

The new column now returns ‘Yes’ or ‘No’ instead of TRUE or FALSE.