使用dplyr有条件地将列中的值替换为另一列中的值 [英] Conditionally replace the values in columns to value in another column using dplyr
问题描述
我非常努力地找到答案,如果出现重复,我深表歉意。
I tried really hard to find an answer to this and I apologize if it's a duplicate.
我将输入一些虚拟数据来解释我的问题。
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
如何有条件地更改 sample1 和 sample2 列中的值,以便如果它们等于1,则采用 a
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.
产生的小标题应如下所示:
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
理想情况下,我不想为每个单独的示例列(我有> 100个示例列)执行此操作,因此一种遍历列的方法会更好(尽管我知道循环是魔鬼)。
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).
谢谢您的帮助!
推荐答案
您可以使用 mutate_at
与 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'))
匹配以 sample
和 mutate_at
将函数 funs(ifelse(。== 1,a,。))
应用于每一列; 。
代表此处的匹配列。
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.
如果确保所有示例列仅包含 1
和 0
,可以将其缩短为:
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
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