Conditionally replace the values in columns to value in another column using dplyr

Question

I tried really hard to find an answer to this and I apologize if it's a duplicate.

I'll make some dummy data to explain my question.

tibble(a=c(0.1, 0.2, 0.3), sample1 = c(0, 1, 1), sample2 = c(1, 1, 0))

# A tibble: 3 x 3
      a sample1 sample2
 <dbl>   <dbl>   <dbl>
1   0.1       0       1
2   0.2       1       1
3   0.3       1       0

How to I conditionally change the values in columns sample1 and sample2 so that if they are equal to one, they take on the value of a .

The resulting tibble should look like this:

# A tibble: 3 x 3
      a sample1 sample2
 <dbl>   <dbl>   <dbl>
1   0.1       0     0.1
2   0.2     0.2     0.2
3   0.3     0.3       0

Ideally I don't want to do this for each individual sample column (I have >100 sample columns), so a way to loop over columns would be better (although I know loops are the devil).

Thanks for your help!

Answer 1

You can use mutate_at with ifelse :

df %>% mutate_at(vars(starts_with('sample')), funs(ifelse(. == 1, a, .)))

# A tibble: 3 x 3
#      a sample1 sample2
#  <dbl>   <dbl>   <dbl>
#1   0.1     0.0     0.1
#2   0.2     0.2     0.2
#3   0.3     0.3     0.0

vars(starts_with('sample')) matches all columns that starts with sample and mutate_at applies the function funs(ifelse(. == 1, a, .)) to each column; . stands for the matched column here.

---

If you are sure all the samples columns contain only 1 and 0 , it can be shortened as:

df %>% mutate_at(vars(starts_with('sample')), funs(. * a))

# A tibble: 3 x 3
#      a sample1 sample2
#  <dbl>   <dbl>   <dbl>
#1   0.1     0.0     0.1
#2   0.2     0.2     0.2
#3   0.3     0.3     0.0

Answer 2

Non-dplyr solution using which() :

> t=tibble(a=c(0.1, 0.2, 0.3), sample1 = c(0, 1, 1), sample2 = c(1, 1, 0))

> whichRows=which(t$sample1==t$sample2)

> t[whichRows,c('sample1','sample2')]<-t[whichRows,'a']

> t
# A tibble: 3 x 3
      a sample1 sample2
  <dbl>   <dbl>   <dbl>
1   0.1     0.0     1.0
2   0.2     0.2     0.2
3   0.3     1.0     0.0