[SOLVED] avoid creating duplicate variable names in function

Issue

I have a dataframe and a function that creates a new variable, adds it to the dataframe and then assigns the dataframe back to the global environment. The problem is that if I rerun the function it creates a duplicate of the variable.

library(tidyverse)
library(rms)
set.seed(10)
ds <- data.frame(
  ftime = rexp(200),
  fstatus = sample(0:1,200, replace = TRUE),
  x1 = runif(200),
  x2 = runif(200),
  x3 = factor(sample(LETTERS[1:3], size = 200, replace = TRUE)))
ds
#model
s <- Surv(ds$ftime, ds$fstatus == 1) 
fit <- cph(s ~ x1 + x2 + x3, data = ds, surv = TRUE, x = TRUE, y = TRUE)

#function to add prediction to dataset
pred_fun <- function(time_to_sur, model) {
  
  pred_data <- ds[, c("x1", "x2", "x3")] %>% 
    mutate(ftime = time_to_sur,
           fstatus = 1) %>%   
    as.data.frame()
  
  ds$pred_var_tmp <-
    rms::survest(model, times = time_to_sur,
                 newdata = pred_data,
                 se.fit = FALSE, what = "survival")$surv
  
  #rename variable
  pred_var <- paste0("pred_prob_", as.character(time_to_sur), "_rms")
  names(ds)[names(ds) == "pred_var_tmp"] <- pred_var
  
  #assign dataset back to global environment
  assign("ds", ds, env = .GlobalEnv) 
}

The function works as it should:

pred_fun(time_to_sur = 0.2, fit)
names(ds)
# [1] "ftime"             "fstatus"           "x1"               
# [4] "x2"                "x3"                "pred_prob_0.2_rms"

But if I rerun it again, it creates a duplicate of the variable

pred_fun(time_to_sur = 0.2, fit)
names(ds)
# [1] "ftime"             "fstatus"           "x1"               
# [4] "x2"                "x3"                "pred_prob_0.2_rms"
# [7] "pred_prob_0.2_rms"

This is to be expected because the function create a new variable first with a different name and then assigns the name after. I thought the following might work in the function but it doesn’t:

ds$eval(substitute(paste0("pred_prob_", as.character(tt), "_rms"))) <-
    rms::survest(model, times = time_to_sur,
                 newdata = pred_data,
                 se.fit = FALSE, what = "survival")$surv

How can I fix this and what is best practices in this situation?

Thanks

Solution

Thanks to @G. Grothendieck and @Limey, the following simplification works (pred_fun_final) although I do get a warning message.

#original function in OP
pred_fun_original <- function(time_to_sur, model) {
  
  pred_data <- ds[, c("x1", "x2", "x3")] %>% 
    mutate(ftime = time_to_sur,
           fstatus = 1) %>%   
    as.data.frame()
  
  ds$pred_var_tmp <-
    rms::survest(model, times = time_to_sur,
                 newdata = pred_data,
                 se.fit = FALSE, what = "survival")$surv
  
  #rename variable
  pred_var <- paste0("pred_prob_", as.character(time_to_sur), "_rms")
  names(ds)[names(ds) == "pred_var_tmp"] <- pred_var

  assign("ds", ds, env = .GlobalEnv) 
}
pred_fun_original(time_to_sur = 0.2, fit)

#save created variable
test1 <- ds$pred_prob_0.2_rms

#remove pred_prob_0.2_rms
ds <- ds %>% 
  select(-pred_prob_0.2_rms)

New function with warning:

#fixed function
pred_fun_final <- function(data, time_to_sur, model) {
  
  newName <- paste0("pred_prob_", as.character(time_to_sur), "_rms")
  pred_data <- data[, c("x1", "x2", "x3")] %>% 
    mutate(ftime = time_to_sur,
           fstatus = 1) %>%   
    as.data.frame()
  
  data <- data %>% 
    mutate({{newName}} := rms::survest(model, times = time_to_sur,
                                       newdata = pred_data,
                                       se.fit = FALSE, what = "survival")$surv)
  
  data
}
ds <- pred_fun_final(ds, time_to_sur = 0.2, fit)
# Warning message:
# Problem with `mutate()` column `pred_prob_0.2_rms`.
# i `pred_prob_0.2_rms = ...$NULL`.

#save variable
test2 <- ds$pred_prob_0.2_rms

The two variables are not identical but that is because one is named and the other is not (as.numeric() would fix this). It doesn’t explain the warning message though.

identical(test1, test2)
#FALSE
str(test1)
#  num [1:200] 0.906 0.9 0.884 0.884 0.886 ...
str(test2)
#  Named num [1:200] 0.906 0.9 0.884 0.884 0.886 ...
#  - attr(*, "names")= chr [1:200] "1" "2" "3" "4" ...

Answered By – user63230

Answer Checked By – Terry (BugsFixing Volunteer)