CODEWITHSUNDEEP
r
user13589693
user13589693

Reputation: 369

Replacing string in multiple dataframes with lapply

I am trying to replace string in multiple dataframes saved in a list with another string. Below is a representative code for what I need. In the example, I am trying to replace the word "white" with "blue" in dat1 and dat2, but the replacement is not working. Is the issue with my indexing of df.list? I tried indexing the df.list$D in as.character(), but an error pops up.

dat1 <- data.frame(c(1,2,3,4), c(10, 20, 30, 40),
                   c(100, 200, 300, 400), c("red G white 40 R3", "red G white 40 R5", 
                                            "red H white 40 R7", "red H white 40 R10"))
dat2 <- data.frame(c("red G white 40 R3", "red G white 40 R5", 
                      "red H white 40 R7", "red H white 40 R10"))

colnames(dat1) <- c("A", "B", "C", "D")
colnames(dat2) <- c("D")

df.list <- list(dat1, dat2)

for(i in 1:length(df.list)){
  df.list[[i]]$D <- lapply(df.list, function(df.list) sub("white", "blue",
                                                                 as.character(df.list$D), fixed = TRUE))
}

Upvotes: 0

Views: 366

Answers (2)

akrun
akrun

Reputation: 887901

We can use transform in base R

df.list <- lapply(df.list, transform, D = sub('white', 'blue', D))

Or using tidyverse

library(dplyr)
library(purrr)
library(stringr)
df.list <- map(df.list, ~ .x %>%
                           mutate(D = str_replace(D, 'white', 'blue')))

Upvotes: 0

Ronak Shah
Ronak Shah

Reputation: 389275

Don't use for loop and lapply. Use either of them : 

df.list <- lapply(df.list, function(x) {x$D <- sub('white', 'blue', x$D);x})
df.list

#[[1]]
#  A  B   C                 D
#1 1 10 100  red G blue 40 R3
#2 2 20 200  red G blue 40 R5
#3 3 30 300  red H blue 40 R7
#4 4 40 400 red H blue 40 R10

#[[2]]
#                  D
#1  red G blue 40 R3
#2  red G blue 40 R5
#3  red H blue 40 R7
#4 red H blue 40 R10

Use gsub if you want to replace multiple occurrences of 'white' with 'blue'.

To get data back to individual dataframes, name the list and use list2env.

names(df.list) <- paste0('dat', 1:2)
list2env(df.list, .GlobalEnv)

Upvotes: 1

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