R: check multiple variables using 'for' loop and 'case_when.'

Question

I have a dataset DT as below:
category: number 1-9
xxx, yyy, zzz: binary (0,1)

category xxx yyy zzz
8         1   0   0
1         0   0   0
4         0   1   1
9         0   0   1
8         0   1   0

I would like to check multiple conditions using 'for' loop and 'case_when.'
So, I wish the data shows at the end

category xxx yyy zzz result_xxx result_yyy result_zzz
8         1   0   0       8           0          0
1         0   0   0       0           0          0
4         0   1   1       0           4          4 
9         0   0   1       0           0          9 
8         0   1   0       0           8          0

To do it, I wrote a code below:

condition.vars <- c("xxx", "yyy", "zzz")

for(i in condition.vars){
  browser()
  DT <- DT[, condition:= case_when(
    ([[i]] == 1 & category ==1) ~ 1,
    ([[i]] == 1 & category ==2) ~ 2,
    ([[i]] == 1 & category ==3) ~ 3,
    ([[i]] == 1 & category ==4) ~ 4,
    ([[i]] == 1 & category ==5) ~ 5,
    ([[i]] == 1 & category ==6) ~ 6,
    ([[i]] == 1 & category ==7) ~ 7,
    ([[i]] == 1 & category ==8) ~ 8,
    ([[i]] == 1 & category ==9) ~ 9,
    TRUE ~ 0
  )]
  setnames(DT, "condition", paste0("result", i))
   
}

And as you expect, it does not work.
Would you please help me to correct my code?

Ronak Shah · Accepted Answer · 2021-01-16 08:03:51Z

2

You don't need a for loop or case_when. If you have a dataframe you can simplify this as :

condition.vars <- c("xxx", "yyy", "zzz")
DT[paste0('result_', condition.vars)] <- DT$category * DT[condition.vars]

#  category xxx yyy zzz result_xxx result_yyy result_zzz
#1        8   1   0   0          8          0          0
#2        1   0   0   0          0          0          0
#3        4   0   1   1          0          4          4
#4        9   0   0   1          0          0          9
#5        8   0   1   0          0          8          0

If DT is data.table you can do :

library(data.table)
DT[, paste0('result_', condition.vars):= category * .SD,.SDcols = condition.vars]

answered Jan 16, 2021 at 8:03

Ronak Shah

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2 Comments

ikryong Over a year ago

Thank you @Ronak Shah. somehow the first does not work but the second suggestion works! I also need to develop seeing data from many perspectives. can I ask you one more? if 'category' was not number but the character, then wouldn't I need to use "case_when"?

Ronak Shah Over a year ago

The first one is for dataframes and since you have datatable the second answer works. I would still not use case_when for characters, there are other ways with lapply that can be used if you have characters. You can have lot of characters of any length. Writing each condition one by one with case_when is not feasible here.

akrun · Accepted Answer · 2021-01-16 19:29:25Z

0

We can use tidyverse

library(dplyr)
DT %>% 
     mutate(across(c(xxx, yyy, zzz), ~ 
                category * ., .names = "result_{.col}"))

answered Jan 16, 2021 at 19:29

akrun

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Comments

ThomasIsCoding · Accepted Answer · 2021-01-16 23:30:59Z

0

Here is a data.table option

setDT(df)[,
  c(
    df,
    setNames(category * .SD, paste0("result_", names(.SD)))
  ),
  .SDcols = xxx:zzz
]

which gives

   category xxx yyy zzz result_xxx result_yyy result_zzz
1:        8   1   0   0          8          0          0
2:        1   0   0   0          0          0          0
3:        4   0   1   1          0          4          4
4:        9   0   0   1          0          0          9
5:        8   0   1   0          0          8          0

answered Jan 16, 2021 at 23:30

ThomasIsCoding

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