问题描述
假设我有2个数据帧,其结构如下:
Suppose I have 2 dataframes structured as such:
组:
P1 P2 P3 P4
123 213 312 231
345 123 213 567
INDIVIDUAL_RESULTS:
INDIVIDUAL_RESULTS:
ID SCORE
123 23
213 12
312 11
213 19
345 10
567 22
我要添加一个 GROUPS
列,这是它们各自结果的总和:
I want to add a column to the GROUPS
which is a sum of each of their individual results:
P1 P2 P3 P4 SCORE
123 213 312 231 65
我尝试使用各种合并
技术,但实际上只是一团糟。我觉得有一个我不知道的简单解决方案,非常感谢您提供一些指导!
I've tried using various merge
techniques, but have really just created a mess. I feel like there's a simple solution I just don't know about, would really appreciate some guidance!
推荐答案
d1=read.table(text="
P1 P2 P3 P4
123 213 312 231
345 123 213 567",h=T)
d2=read.table(text="
ID SCORE
123 23
213 12
312 11
231 19
345 10
567 22",h=T)
我将使用 apply
和 match
函数。 Apply将对d1的每一行应用match函数,match将从d1和d2 $ ID(它们的索引)行中找到匹配值,然后在这些索引处获取d2 $ SCORE中的值。最后,我们将它们汇总。
I will be using the apply
and match
functions. Apply will apply the match function to each row of d1, match will find the matching values from the row of d1 and d2$ID (their indices) and then take the values in d2$SCORE at those indices. In the end we sum them up.
d1$SCORE=apply(d1,1,function(x){
sum(d2$SCORE[match(x,d2$ID)])
})
和结果
P1 P2 P3 P4 SCORE
1 123 213 312 231 65
2 345 123 213 567 67
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