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The gsub() function in R can be used to replace multiple patterns in a row. This is done by providing a vector of patterns to be matched and a vector of replacement values that correspond to the patterns. gsub() will then replace all occurrences of the specified patterns with the corresponding replacement values. For example, gsub(c(‘pattern1’, ‘pattern2’), c(‘replacement1’, ‘replacement2’), x) will replace all occurrences of pattern1 with replacement1, and all occurrences of pattern2 with replacement2. This is a useful way to quickly make multiple replacements to a string in a single line of code.
The function in R can be used to replace all occurrences of a certain pattern within a string in R.
To replace multiple patterns at once, you can use a nested gsub() statement:
df$col1 <- gsub('old1', 'new1',
gsub('old2', 'new2',
gsub('old3', 'new3', df$col1)))
However, a much faster method is the stri_replace_all_regex() function from the stringi package, which uses the following syntax:
library(stringi) df$col1 <- stri_replace_all_regex(df$col1, pattern=c('old1', 'old2', 'old3'), replacement=c('new1', 'new2', 'new3'), vectorize=FALSE)
The following examples show how to use each method in practice.
Method 1: Replace Multiple Patterns with Nested gsub()
Suppose we have the following data frame in R:
#create data frame
df <- data.frame(name=c('A', 'B', 'B', 'C', 'D', 'D'),
points=c(24, 26, 28, 14, 19, 12))
#view data frame
df
name points
1 A 24
2 B 26
3 B 28
4 C 14
5 D 19
6 D 12
We can use a nested gsub() statement to replace multiple patterns in the name column:
#replace multiple patterns in name column
df$name <- gsub('A', 'Andy',
gsub('B', 'Bob',
gsub('C', 'Chad', df$name)))
#view updated data frame
df
name points
1 Andy 24
2 Bob 26
3 Bob 28
4 Chad 14
5 D 19
6 D 12
Notice that A, B, and C in the name column have all been replaced with new values.
Method 2: Replace Multiple Patterns with stringi
A much faster way to replace multiple patterns is by using the stri_replace_all_regex() function from the stringi package.
The following code shows how to use this function:
library(stringi) #replace multiple patterns in name column df$name <- stri_replace_all_regex(df$name, pattern=c('A', 'B', 'C'), replacement=c('Andy', 'Bob', 'Chad'), vectorize=FALSE) #view updated data frame df name points 1 Andy 24 2 Bob 26 3 Bob 28 4 Chad 14 5 D 19 6 D 12
Notice that the resulting data frame matches the one from the previous example.
The following tutorials explain how to perform other common operations in R: