问题描述
data [，allkneePR:= Reduce(`|`，lapply(.SD，`==`，"0082"))，.SDcols = PR1:PR3]
嘿，我试图在data.table(数据集很大)中的一系列行和列中寻找不同的诊断c("0082"，"0083"，"0084").如果任何一个PR1:PR3列中的值之一是"0082"，"0083"或"0084"，则我希望另一列指示为true.现在，这适用于上面的代码，但是我试图添加多个诊断，而不仅仅是"0082".我尝试了不起作用的any()函数，仅使用向量c("0082"，"0083"，"0084")无效.
Hey, I'm trying to look for different diagnoses c("0082", "0083", "0084") across a range of rows and columns in data.table (the dataset is huge). If one of the values is "0082" or "0083" or "0084" in any of the columns PR1:PR3 I want another column that indicates true. Right now this works with the above code, but I am trying to add in multiple diagnoses, not just "0082". I tried the any() function which doesn't work, and just using a vector c("0082", "0083", "0084") doesn't work.
有什么想法吗?谢谢！
有趣的练习数据集在这里:
Fun practice dataset is here:
data <- as.data.table(data.frame(PR1 = c("0081", "0082", "0083", "0084", "8154"), PR2 = c("12","0084", "1","3", "9"), PR3 = c("9", "12", "25", "0083", "8154")))
data[, allkneePR := Reduce(`|`, lapply(.SD, `==`, "0082")), .SDcols=PR1:PR3]
data
推荐答案
我们可以使用％in％代替 == 来比较长度大于1的向量
We can use %in% instead of == for comparing a vector of length greaterr than 1
library(data.table)
data[, allkneePR := Reduce(`|`, lapply(.SD, `%in%`,
c("0082", "0083", "0084"))), .SDcols=PR1:PR3]
data
# PR1 PR2 PR3 allkneePR
#1: 0081 12 9 FALSE
#2: 0082 0084 12 TRUE
#3: 0083 1 25 TRUE
#4: 0084 3 0083 TRUE
#5: 8154 9 8154 FALSE
如果列是字符，则可以将％in％更改为％chin％
If the columns are character, can change %in% to %chin%
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