CODEWITHSUNDEEP
rpurrr
Leonardo Donato Nunes
Leonardo Donato Nunes

Reputation: 148

Use purrr::map to rewrite a vector as in for loop

How can I use purrr::map() to return the result of the for loop of the example:

vct_string <- c("old ccar","new carr", "house", "oold house")

df_correction <- data.frame(
  pattern  = c("ccar", "carr", "oold"),
  replacement = c("car", "car", "old"),
  stringsAsFactors = FALSE
)

for(i in 1:nrow(df_correction)){
  vct_string <- pmap(df_correction, gsub, x = vct_string)[[i]]
}

> vct_string
[1] "old car"   "new car"   "house"     "old house"

Upvotes: 3

Views: 147

Answers (4)

Onyambu
Onyambu

Reputation: 79198

Actually, you do not need any of the ReduceMap functions. Just use str_replace_all its vectorized

library(stringr)
str_replace_all(vct_string, set_names(df_correction$replacement, df_correction$pattern))

[1] "old car"   "new car"   "house"     "old house"

Upvotes: 4

AnilGoyal
AnilGoyal

Reputation: 26218

You have to recursively modify your vector so in my opinion this is classic case of usage of reduce family function here. So do this, where you will have to pass your vector to .init argument of purrr::reduce to get the desired output

purrr::reduce(seq(nrow(df_correction)), .init = vct_string, ~ gsub(df_correction$pattern[.y], df_correction$replacement[.y], .x))

#> [1] "old car"   "new car"   "house"     "old house"

This will even do multiple replacements in elements of given vector. see this

#modified example
vct_string <- c("old ccar","new carr", "house", "oold carr")

purrr::reduce(seq(nrow(df_correction)), .init = vct_string, ~ gsub(df_correction$pattern[.y], df_correction$replacement[.y], .x))
[1] "old car" "new car" "house"   "old car"

Upvotes: 3

Anoushiravan R
Anoushiravan R

Reputation: 21908

Here is how you could do it with base::Reduce:

Reduce(function(x, y) {
  gsub(df_correction[y, 1], df_correction[y, 2], x)
}, init = vct_string, 1:nrow(df_correction))

[1] "old car"   "new car"   "house"     "old house"

Upvotes: 1

Jeff Parker
Jeff Parker

Reputation: 1969

First write a function for the replacements

word_correct <- function(string) {
  df_correction <- data.frame(
    pattern  = c("old ccar", " new carr", "oold house", "house"), # changed from OP
    replacement = c("car", "car", "old", "house"),
    stringsAsFactors = FALSE
  )
  df_correction[ which(df_correction$pattern == string), "replacement"]
}

# Testing
word_correct("oold")
word_correct("ccar")

Then you can pass that function as an argument in purrr::map

map_chr(vct_string, word_correct) # using map_chr to return a vector instead of a list which is what map returns

Since you are using a mapping table to replace individual words, you can actually use map in a second function to get your desired results.

vct_string <- c("old ccar","new carr", "house", "oold house")

single_word_correct <- function(string) {
  
  df_correction <- data.frame(
    pattern  = c("ccar", "carr", "oold"),
    replacement = c("car", "car", "old"),
    stringsAsFactors = FALSE
  )
  if(string %in% df_correction$pattern){
    df_correction[ which(df_correction$pattern == string), "replacement"]
  } else {
    string
  }
}
multi_word_correct <- function(string){
  strings <- strsplit(string, " ")[[1]]
  paste(map_chr(strings, single_word_correct), collapse = " ")
}

map_chr(vct_string, multi_word_correct)

Upvotes: 1

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