Copy value from one column to the next given a condition

July 4, 2022

I have binary data as below:

ID <- c("A", "B", "C", "D", "E", "F")
Q0 <- c(0, 0, 0, 0, 0, 0)
Q1 <- c(0, 1, 0, 0, NA, 1) 
Q2 <- c(0, NA, 1, 0, NA, 1) 
Q3 <- c(0, NA, NA, 1, NA, 1) 
Q4 <- c(0, NA, NA, 1, NA, 1)

dta <- data.frame(ID, Q0, Q1, Q2, Q3, Q4)

If there is 1 for a row in one of the columns, all the subsequent columns should be 1 as well. If there is 0 or NA, the next column should stay as is. I have written the code below:

dta2  <- dta %>% 
  mutate(Q2 = case_when(Q1 == 1 ~ 1, 
                        TRUE ~ Q2))

dta3  <- dta2 %>% 
  mutate(Q3 = case_when(Q2 == 1 ~ 1, 
                        TRUE ~ Q3))

dta4  <- dta3 %>% 
  mutate(Q4 = case_when(Q3 == 1 ~ 1, 
                        TRUE ~ Q4))

It works fine, and the output looks as intended:

ID    Q0    Q1    Q2    Q3    Q4
A     0     0     0     0     0
B     0     1     1     1     1
C     0     0     1     1     1
D     0     0     0     1     1
E     0     NA    NA    NA    NA
F     0     1     1     1     1

My question is: is there a more elegant way to do this? Perhaps using apply or even a for loop?

>Solution :

Yet another dplyr + purrr option could be:

dta %>%
 mutate(pmap_dfr(across(-ID), ~ `[<-`(c(...), seq_along(c(...)) > match(1, c(...)), 1)))

  ID Q0 Q1 Q2 Q3 Q4
1  A  0  0  0  0  0
2  B  0  1  1  1  1
3  C  0  0  1  1  1
4  D  0  0  0  1  1
5  E  0 NA NA NA NA
6  F  0  1  1  1  1