我有一个如下所示的数据集：
1. ID RESULT_DATE Hyperkalemia Is.Hemolyzed
2. 1 5/27/2008 2 FALSE
3. 1 5/28/2008 2 FALSE
4. 1 5/29/2008 2 FALSE
5. 1 5/29/2008 2 FALSE
6. 1 5/29/2008 3 FALSE
7. 1 5/30/2008 2 FALSE
8. 1 6/15/2008 4 FALSE
9. 1 10/14/2014 1 FALSE
10. 1 10/16/2014 NA FALSE
11. 2 8/12/2013 2 FALSE
12. 3 2/26/2012 2 FALSE
13. 3 2/27/2012 2 FALSE
14. 3 4/18/2012 3 FALSE
15. 3 4/18/2012 4 FALSE
16. 3 4/21/2012 4 FALSE
17. 3 4/23/2012 4 FALSE
18. 3 4/27/2012 4 FALSE
19. 3 5/8/2012 4 FALSE
20. 3 5/12/2012 4 FALSE
21. 3 5/15/2012 4 FALSE
22. 3 5/15/2012 NA FALSE
我想找到高钾血症评分为3或4且为a的钾测试的次数。在同一天重复溶血= FALSE（必须按患者ID计算重复次数）目标是总次数测试符合重复次数，然后是重复次数的总次数。
有人可以帮我翻译我的伪代码到R代码吗？
# data.frame = pots
# for every row (sorted by patient and result date)
for (i in 1:nrow(pots){
# for each patient (sorted by result date)
# how do I do I count the rows for the individual patient?
for (i in 1:length(pots$ID)) {
# assign result date to use for calculation
result_date = pots$result_date
# if Hyperkalemia = 3 or 4
if (Hyperkalemia == 3 | Hyperkalemia == 4)
# go find the next result for patient where is.Hemolyzed = FALSE
# how do I get the next result?
for (i+1)
# assign date to compare to first date
next_result_date = pots$result_date
if next_result_date > result_date
then repeated_same_day <- FALSE
else if result_date == result_date
then repeated_same_day <- TRUE
}
}
目标：我想计算一次3级或4级非溶血性钾结果在24小时内进行另一次钾测试的频率（通过唯一ID）（我现在使用的是另一个字段 - 我想我可以添加一些日期函数计算24小时）。
编辑：我确实最终使用了for循环！分享以防万一对任何人都有帮助。后来我确实看到了一个错误，但对于我的数据集，它没问题。
library(dplyr)
pots <- read.csv("phis_potassium-2015-07-30.csv",
head=TRUE, stringsAsFactors = FALSE)
pots <- arrange(pots, MRN, COLLECTED_DATE)
pots$Hyperkalemia[is.na(pots$Hyperkalemia)] <- 0
pots$repeated_wi24hours <- NA
pots$met_criteria <- NA
pots$next_test_time_interval <- NA
# data.frame = pots
# for every patient (sorted by patient and collected date)
for (mrn in unique(pots$MRN)){
# for each row for each patient (sorted by collected date)
for (i in 1:length(pots$MRN[pots$MRN == pots$MRN[mrn]])) {
# if Hyperkalemia = 3 or 4 AND Is.Hemolyzed == FALSE
if((pots$Hyperkalemia[i] == 3 | pots$Hyperkalemia[i] == 4) & pots$Is.Hemolyzed[i] == FALSE){
pots$met_criteria[i] <- TRUE
# get time interval between tests
pots$next_test_time_interval[i] <- difftime(pots$COLLECTED_DATE[i+1], pots$COLLECTED_DATE[i], units = "hours")
# if next date is within 24 hours, then test repeated
if (pots$next_test_time_interval[i] <= 24 ){
pots$repeated_wi24hours[i] <- TRUE
}
else {
pots$repeated_wi24hours[i] <- FALSE
}
}
}
}
期望的输出
ID RESULT_DATE Hyperkalemia Is.Hemolyzed Met_criteria Repeated
1 5/27/2008 2 FALSE
1 5/28/2008 2 FALSE
1 5/29/2008 2 FALSE
1 5/29/2008 2 FALSE
1 5/29/2008 3 FALSE TRUE FALSE
1 5/30/2008 2 FALSE
1 6/15/2008 4 FALSE
1 10/14/2014 1 FALSE
2 8/12/2013 2 FALSE
3 2/26/2012 2 FALSE
3 2/27/2012 2 FALSE
3 4/18/2012 3 FALSE TRUE TRUE
3 4/18/2012 4 FALSE TRUE FALSE
3 4/21/2012 4 FALSE TRUE FALSE
答案 0 :(得分：2)
这个怎么样：
metCriteria <- function( dfPots )
{
(dfPots$Hyperkalemia==3 | dfPots$Hyperkalemia==4) & !dfPots$Is.Hemolyzed
}
#----------------------------------------------------------------------
pots <- read.table(filename, header=TRUE)
d <- paste( as.character(pots$RESULT_DATE),
"_ID",
as.character(pots$ID))
lastOccurence <- unlist(lapply(d,function(x){which.min(diff(c(d,FALSE)==x))}))
pots <- cbind(pots, data.frame( Met_criteria = rep(FALSE,nrow(pots))),
Repeated = rep(TRUE ,nrow(pots)) )
pots$Repeated[lastOccurence] <- FALSE
pots$Met_criteria[which(metCriteria(pots))] <- TRUE
将日期和ID粘贴在矢量＆＃34; d＆＃34;中。 向量的第i个组成部分＆＃34; lastOccurence＆＃34;是日期/ ID对d [i]发生的行号或最后一次。
数据框＆＃34; pot＆＃34;由两列扩展，＆＃34; Met_criteria＆＃34;和＆＃34;重复＆＃34;。
示例：
> pots
ID RESULT_DATE Hyperkalemia Is.Hemolyzed Met_criteria Repeated
1 1 5/27/2008 2 FALSE FALSE FALSE
2 1 5/28/2008 2 FALSE FALSE FALSE
3 3 5/28/2008 2 FALSE FALSE FALSE
4 1 5/29/2008 2 FALSE FALSE TRUE
5 1 5/29/2008 2 FALSE FALSE TRUE
6 1 5/29/2008 3 FALSE TRUE FALSE
7 2 5/29/2008 4 FALSE TRUE FALSE
8 1 5/30/2008 2 FALSE FALSE FALSE
9 1 6/15/2008 4 FALSE TRUE FALSE
10 1 10/14/2014 1 FALSE FALSE FALSE
11 1 10/16/2014 NA FALSE FALSE FALSE
12 2 8/12/2013 2 FALSE FALSE FALSE
13 3 2/26/2012 2 FALSE FALSE FALSE
14 3 2/27/2012 2 FALSE FALSE FALSE
15 3 4/18/2012 3 FALSE TRUE TRUE
16 3 4/18/2012 4 FALSE TRUE FALSE
17 3 4/21/2012 4 FALSE TRUE FALSE
18 3 4/23/2012 4 FALSE TRUE FALSE
19 3 4/27/2012 4 FALSE TRUE FALSE
20 3 5/8/2012 4 FALSE TRUE FALSE
21 3 5/12/2012 4 FALSE TRUE FALSE
22 3 5/15/2012 4 FALSE TRUE TRUE
23 3 5/15/2012 NA FALSE FALSE FALSE
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