这是对How to lookup and sum multiple columns in R的后续行动:
我有3个数据帧,
组:
P1 P2 P3 P4
"Joe" "Sally" "A.J." "Mary"
"Cory" "Joe" "Sally" "Katy"
名称:
ID NAME
123 "Joe"
213 "Sally"
312 "A.J."
231 "Mary"
345 "Cory"
567 "Katy"
个人结果:
ID SCORE
123 23
213 12
312 11
231 19
345 10
567 22
我的目标是在Groups
中用SCORE
列创建一个新列,该列是该组中每个结果的总和。
P1 P2 P3 P4 SCORE
"Joe" "Sally" "A.J." "Mary" 65
按照上面提到的问题的答案示例,我尝试了以下
groups$score = apply(groups, 1, function(x){
sum(Individual_Results$SCORE[match(match(x, Names$Name), Individual_Results$ID)])
})
不幸的是,结果是创建了新列,但每个分数的结果都是NA
。
如果我了解如何正确使用apply
和match
,我想做的就是将apply
函数传递给每一行,并传递x
( Name
)作为第一个match
函数的参数,以获取ID
,然后将返回的ID
与第二个match
进行匹配以获取分数-将每一行的所有分数相加。
我认为我超级亲密,但还远远不够。感谢任何帮助!
答案 0 :(得分:2)
这可以解决问题。
请注意,您不需要data.table
。我只是用它来使示例可重现
require(data.table)
Groups <- data.frame(fread('"P1","P2","P3","P4"
"Joe","Sally","A.J.","Mary"
"Cory","Joe","Sally","Katy"'))
Names <- data.frame(fread('ID,NAME
123,"Joe"
213,"Sally"
312,"A.J."
231,"Mary"
345,"Cory"
567,"Katy"'))
Individual_Results <- data.frame(fread('ID,SCORE
123,23
213,12
312,11
231,19
345,10
567,22'))
Groups$SCORE <- apply(Groups, 1, function(x){
sum(Individual_Results$SCORE[match(Names$ID[match(x, Names$NAME)], Individual_Results$ID)])
})
# Inspect groups:
Groups
# P1 P2 P3 P4 SCORE
# 1 Joe Sally A.J. Mary 65
# 2 Cory Joe Sally Katy 67