问题
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!
回答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
回答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
来源：https://stackoverflow.com/questions/46851738/conditionally-replace-the-values-in-columns-to-value-in-another-column-using-dpl