Improve performance of replacing multiple strings-CodePudding

I am masking phone numbers and personal names on my raw data. I already asked and got the answer here for my work about phone numbers.

In the case of masking personal names, I have the following code:

x = c("010-1234-5678",
      "John 010-8888-8888",
      "Phone: 010-1111-2222",
      "Peter 018.1111.3333",
      "Year(2007,2019,2020)",
      "Alice 01077776666")

df = data.frame(
  phoneNumber = x
)

delName = c("John", "Peter", "Alice")

for (name in delName) {
  df$phoneNumber <- gsub(name, "anonymous", df$phoneNumber)
}

That code is not a problem for me,

> df
              phoneNumber
1           010-1234-5678
2 anonymous 010-8888-8888
3    Phone: 010-1111-2222
4 anonymous 018.1111.3333
5    Year(2007,2019,2020)
6   anonymous 01077776666

but I have over 10,000 personal names to mask. R is working 789th process now. Time can solve it, but I would like to know the way to reduce processing time. I searched foreach, but I do not know how to tune my original code above.

CodePudding user response：

You could try this without a loop first and paste strings together with an or \.

(delNamec <- paste(delName, collapse='|'))
# [1] "John|Peter|Alice"

gsub(delNamec, 'anonymous', df$phoneNumber)
# [1] "010-1234-5678"          
# [2] "anonymous 010-8888-8888"
# [3] "Phone: 010-1111-2222"   
# [4] "anonymous 018.1111.3333"
# [5] "Year(2007,2019,2020)"   
# [6] "anonymous 01077776666"

Runs in a blink of an eye, even with 100k rows.

df2 <- df[sample(nrow(df), 1e5, replace=T),,drop=F]
dim(df2)
# [1] 100000      1
system.time(gsub(delNamec, 'anonymous', df2$phoneNumber))
#  user  system elapsed 
# 0.129   0.000   0.129

CodePudding user response：

Here is another option using stringr.

library(stringr)

str_replace_all(
  string = df$phoneNumber,
  pattern = paste(delName, collapse = '|'),
  replacement = "anonymous"
)