How to create multiple new column using apply in R?-CodePudding

I want to create multiple columns using the apply function. The idea is to use the apply to create new columns using paste0 to define the name. Follows an example:


Name <- c("Jon", "Bill", "Maria", "Ben", "Tina")
Age <- c(23, 41, 32, 58, 26)
Number <- 1:4

df <- data.frame(Name, Age)

creating_columns <- function(number){
  df[paste0("new_",number)] <- number
  
 return(df) 
}

lapply(Number,creating_columns)

The code doesn't work. I have just a list of four different data frames, and in each one, I have a new column but I wanted the final data with all new columns. I can use for to create this, but my real data frame is too big so it takes too long. Follows the code that works:

for (number in Number){
  df[paste0("new_",number)] <- number
}

I want the following:

   Name Age new_1 new_2 new_3 new_4
1   Jon  23     1     2     3     4
2  Bill  41     1     2     3     4
3 Maria  32     1     2     3     4
4   Ben  58     1     2     3     4
5  Tina  26     1     2     3     4

CodePudding user response：

apply/lapply would not be a great way to approach this. Variables modified in a function do not change outside that function thanks to scoping rules. It would be better to generate your new columns however you like, then bind them to the original data. For example

cbind(df, setNames(as.list(Number), paste0("new_", Number)))
#    Name Age new_1 new_2 new_3 new_4
# 1   Jon  23     1     2     3     4
# 2  Bill  41     1     2     3     4
# 3 Maria  32     1     2     3     4
# 4   Ben  58     1     2     3     4
# 5  Tina  26     1     2     3     4

Here we recreate a list from your numbers which act as the column values and then use setNames to give the columns new names

CodePudding user response：

You can use <<- inside your function and will get your result as for loop , but it is not recommended to change the parent environment from a function

Name <- c("Jon", "Bill", "Maria", "Ben", "Tina")
Age <- c(23, 41, 32, 58, 26)
Number <- 1:4

df <- data.frame(Name, Age)

creating_columns <- function(number){
    df[paste0("new_",number)] <<- number
}

lapply(Number,creating_columns)

output

df

   Name Age new_1 new_2 new_3 new_4
1   Jon  23     1     2     3     4
2  Bill  41     1     2     3     4
3 Maria  32     1     2     3     4
4   Ben  58     1     2     3     4
5  Tina  26     1     2     3     4