这是数据: 示例1:完成
complete <- c("A", "B", "C","J", "C1", "L", "J2", "D", "M", "N")
lst1 <- c(NA, NA, NA, "A", "N", NA,"A", "C", "D", NA )
lst2 <- c(NA, NA, NA,"A", "L", NA, "C1", "J2", "J2", "B")
datf <- data.frame (complete, lst1, lst2, stringsAsFactors = FALSE)
示例2:不完整和重复
complete <- c("A", "B", "C","J", "C1", "L", "C", "D", "M", "N")
lst1 <- c(NA, NA, NA, "A", "N", NA,"A", "C", "D1", NA )
lst2 <- c(NA, NA, NA,"A", "L", NA, "C1", "J2", "J2", "B2")
datf2 <- data.frame (complete, lst1, lst2, stringsAsFactors = FALSE)
我想查看: (1)如果lst1和lst2的成员至少至少出现一次。 如果不存在,那么停止消息会说这个“?”存在于lst1或lst2(无论正确)但不完整。 我的试用版: 例如1
if (datf$lst1 %in% datf$complete | datf$lst2 %in% datf$complete) {
stop ("the subject in lst1 or lst2 must be complete list ")} else {
cat("I am fine")
}
I am fineWarning message:
In if (datf$lst1 %in% datf$complete | datf$lst2 %in% datf$complete) { :
the condition has length > 1 and only the first element will be used
为什么会出现此错误消息,我该怎么压制它?
Example 2:
if (datf2$lst1 %in% datf2$complete | datf2$lst2 %in% datf2$complete) {
stop ("the subject in lst1 or lst2 must be complete list ")} else {
cat("I am fine")
}
Although there is potential errors the error message is same:
I am fineWarning message:
In if (datf2$lst1 %in% datf2$complete | datf2$lst2 %in% datf2$complete) { :
the condition has length > 1 and only the first element will be used
还有一种方法可以提供不匹配的名称作为错误消息的一部分。
(2)如果任何完整成员被公开。
修改
Expected answer:
Example1 <- all members of lst1 and lst2 are also member of complete
expacted message here is "I am fine"
Example2 <-
B2, J2, is member of lst2 but not complete, D1 is member of lst1 but not complete.
complete have two C, so C is duplicated.
The function will stop and print a message
"B2 and J2 are member of lst1, but not in complete
D1 is member of lst2, but not in complete,
check completeness"
"C is duplicated in complete"
答案 0 :(得分:1)
> datf$lst1 %in% datf$complete | datf$lst2 %in% datf$complete
[1] FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
来自?'if'
if的参数是长度为1的逻辑向量,不是NA。
> na.omit(datf2$lst1)[!na.omit(datf2$lst1)%in%datf2$complete]
[1] "D1"
> na.omit(datf2$lst2)[!na.omit(datf2$lst2)%in%datf2$complete]
[1] "J2" "J2" "B2"
> datf2$complete[duplicated(datf2$complete)]
[1] "C"
以上内容应该可以帮助你构建一个功能来完成你的建议。