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The %in% operator in R is a powerful tool used for testing if an element is present in a vector or data frame. It can be used to check if a given element is present in a vector, list, or data frame. It returns a logical vector indicating whether the element is present (TRUE) or not (FALSE). It is used in the form of element %in% vector and can be combined with other operators like & and | to form more complex logical expressions. %in% operator is a vectorized version of the in operator and is more efficient than using the looping construct.
The %in% operator in R allows you to determine whether or not an element belongs to a vector or data frame.
This tutorial provides three examples of how to use this function in different scenarios.
Example 1: Use %in% with Vectors
We can use the %in% operator to determine how many elements of one vector belong to another vector:
#define two vectors of data data1 <- c(3, 5, 7, 7, 14, 19, 22, 25) data2 <- c(1, 2, 3, 4, 5) #produce new vector that contains elements of data1 that are in data2 data1[data1 %in% data2] [1] 3 5
We can see that the values 3 and 5 are the only elements from the vector titled data2 that are in the vector titled data1.
Example 2: Use %in% to filter Data Frames
We can also use the %in% operator to filter for rows in a data frame that contain certain values:
#define data frame df <- data.frame(team=c('A', 'A', 'B', 'B', 'B', 'C'), points=c(67, 72, 77, 89, 84, 97), assists=c(14, 16, 12, 22, 25, 20)) #view data frame df team points assists 1 A 67 14 2 A 72 16 3 B 77 12 4 B 89 22 5 B 84 25 6 C 97 20 #produce new data frame that only contains rows where team is 'B' df_new <- df[df$team %in% c('B'), ] df_new team points assists 3 B 77 12 4 B 89 22 5 B 84 25 #produce new data frame that only contains rows where team is 'B' or 'C' df_new2 <- df[df$team %in% c('B', 'C'), ] df_new2 team points assists 3 B 77 12 4 B 89 22 5 B 84 25 6 C 97 20
Example 3: Use %in% to Create Data Frame Columns
We can also use the %in% operator to create new data frame columns.
For example, the following code shows how to create a new column titled division that places teams ‘A’ and ‘C’ in the ‘East’ and teams ‘B’ in the ‘West’:
library(dplyr) #define data frame df <- data.frame(team=c('A', 'A', 'B', 'B', 'B', 'C'), points=c(67, 72, 77, 89, 84, 97), assists=c(14, 16, 12, 22, 25, 20)) #view data frame df team points assists 1 A 67 14 2 A 72 16 3 B 77 12 4 B 89 22 5 B 84 25 6 C 97 20 #create new column called division df$division = if_else(df$team %in% c('A', 'C'), 'East', 'West') df team points assists division 1 A 67 14 East 2 A 72 16 East 3 B 77 12 West 4 B 89 22 West 5 B 84 25 West 6 C 97 20 East
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