You can use the following basic syntax to select all elements that are not in a list of values in R:

!(data %in% c(value1, value2, value3, ...))

The following examples show how to use this syntax in practice.

Example 1: How to Use “NOT IN” with Vectors

The following code shows how to select all values in a vector in R that are not in a certain list of values:

#define numeric vector
num_data <- c(1, 2, 3, 3, 4, 4, 5, 5, 6)

#display all values in vector not equal to 3 or 4
num_data[!(num_data %in% c(3, 4))]

[1] 1 2 5 5 6

All values that are not equal to 3 or 4 are shown in the output.

Note that we can use the same syntax to select all elements in a vector that are not in a certain list of characters:

#define vector of character data
char_data <- c('A', 'A', 'A', 'B', 'B', 'C', 'C', 'D', 'D', 'D')

#display all elements in vector not equal to 'A', or 'C'
char_data[!(char_data %in% c('A', 'C'))]

[1] "B" "B" "D" "D" "D"

All values that are not equal to ‘A’ or ‘C’ are shown in the output.

Example 2: How to Use “NOT IN” with Data Frames

The following code shows how to select all rows in a data frame in R in which a certain column is not equal to certain values:

#create data frame
df <- data.frame(team=c('A', 'A', 'B', 'B', 'C', 'C', 'D'),
                 points=c(77, 81, 89, 83, 99, 92, 97),
                 assists=c(19, 22, 29, 15, 32, 39, 14))

#view data frame
df

  team points assists
1    A     77      19
2    A     81      22
3    B     89      29
4    B     83      15
5    C     99      32
6    C     92      39
7    D     97      14

#select all rows where team is not equal to 'A' or 'B'
subset(df, !(team %in% c('A', 'B')))

  team points assists
5    C     99      32
6    C     92      39
7    D     97      14

Notice that all rows that do not have an ‘A’ or ‘B’ in the team column are returned.

We can also use similar syntax to select all rows in which a certain column is not equal to certain numeric values:

#create data frame
df <- data.frame(team=c('A', 'A', 'B', 'B', 'C', 'C', 'D'),
                 points=c(77, 81, 89, 83, 99, 92, 97),
                 assists=c(19, 22, 29, 15, 32, 39, 14))

#view data frame
df

  team points assists
1    A     77      19
2    A     81      22
3    B     89      29
4    B     83      15
5    C     99      32
6    C     92      39
7    D     97      14

#select all rows where team is not equal to 'A' or 'B'
subset(df, !(points %in% c(89, 99)))

  team points assists
1    A     77      19
2    A     81      22
4    B     83      15
6    C     92      39
7    D     97      14

Notice that all rows that are not equal to 89 or 99 in the points column are returned.