custom function to call from dataframe for string in R

user_1699549 0
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here is my sample data

#data
a <- c(1,2,3,4,5,6)
b <- c('x','','x~y~z','z','','x')

#created the dataframe
c<-data.frame(a,b)

#viewing the dataframe
c

#output
  a     b
1 1     x
2 2      
3 3 x~y~z
4 4     z
5 5      
6 6     x

My Expected output is

enter image description here

this is what i tried using a function , I tried in creating a new function as below

getC <- function(df, col,y){
  if(df[,col]==y){
    return(y)
  }else if(is.na(df[,col])){
    return("")
  }else if(strsplit(unlist(T_FRM_G[11,4]),'~')==y){
    return(y)
    break
  }
}

#calling the functions and creating a new column x,y,z and the 
functions should split the based on ~ of those respective cells.
c$x <- getC(c,"b","x")
c$y <- getC(c,"b","y")
c$z <- getC(c,"b","z")

the below is the error
> c$x <- getC(c,"b","x")
Warning message:
In if (df[, col] == y) { :
  the condition has length > 1 and only the first element will be used

Please help why i am getting that error and what i should do to avoid those errors.

r
1 Answers

The reason for the warning is based on the behavior of if/else which is not vectorized i.e. it expects a vector of length 1. We could extract the elements as

library(dplyr)
library(purrr)
library(stringr)
library(tidyr)
c %>%
   mutate(out = imap_dfc(setNames(c('x', 'y', 'z'), 
   c('x', 'y', 'z')), ~ str_extract(b, .x))) %>%
   unnest_wider(out, names_sep = ".") %>% 
   rename_with(~ str_remove(.x, 'out\\.'))

-output

# A tibble: 6 × 5
      a b       x     y     z    
  <dbl> <chr>   <chr> <chr> <chr>
1     1 "x"     x     <NA>  <NA> 
2     2 ""      <NA>  <NA>  <NA> 
3     3 "x~y~z" x     y     z    
4     4 "z"     <NA>  <NA>  z    
5     5 ""      <NA>  <NA>  <NA> 
6     6 "x"     x     <NA>  <NA>

Or another option is to create dummy cols and replace the 1s with column values

library(dplyr)
library(fastDummies)
dummy_cols(c, "b", split = "~") %>%
  transmute(a, b, across(starts_with('b_'), 
   ~ case_when(.x == 1 ~ str_remove(cur_column(), "b_"), TRUE ~ ""), 
      .names = "{str_remove(.col, 'b_')}"))

-output

 a     b x y z
1 1     x x    
2 2            
3 3 x~y~z x y z
4 4     z     z
5 5            
6 6     x x

If there are more columns, pass a vector of column names

c <- data.frame(a,b, c = b)
dummy_cols(c, c("b", "c"), split = "~") %>%
   transmute(a, b, c, across(contains("_"),  
 ~case_when(.x == 1 ~ str_remove(cur_column(), "b_|c_"), TRUE ~ "")))
  a     b     c b_x b_y b_z c_x c_y c_z
1 1     x     x   x           x        
2 2                                    
3 3 x~y~z x~y~z   x   y   z   x   y   z
4 4     z     z           z           z
5 5                                    
6 6     x     x   x           x
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