soporific
Reputation: 103
nested looping through rows/columns in r
I have a data set that looks like this:
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
I want find the number of times a potassium test with a Hyperkalemia score of 3 or 4 and an is.HEmolyzed = FALSE was repeated the same day (must count the repeats by patient ID) Objective is the total number of times the test qualified for a repeat and then the total number of times the repeat occurred.
Could someone help me translate my pseudocode into working R code?
# 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$result_date
if next_result_date > result_date
then repeated_same_day <- FALSE
else if result_date == result_date
then repeated_same_day <- TRUE
}
}
goal: I want to calculate how often (by unique ID) a grade 3 or 4 non-hemolyzed potassium result has another potassium test within 24 hours (I'm using a different field now -- I guess I can add some date function to calculate 24 hours).
Edit: I did get it working with for loops eventually!! Sharing in case it is helpful to anyone. Later I did see a mistake, but for my data set it was okay.
library(dplyr)
pots <- read.csv("phis_potassium-2015-07-30.csv",
head=TRUE, stringsAsFactors = FALSE)
pots <- arrange(pots, MRN, COLLECTED_DATE)
pots$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
}
}
}
}
Desired output
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
Upvotes: 0
Views: 501
Answers (1)
mra68
Reputation: 2960
How about this:
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
The dates and ID's are pasted together in the vector "d". The i-th component of the vector "lastOccurence" is the row number where the date/ID-pair d[i] occures or the last time.
The data frame "pots" is extended by two columns, "Met_criteria" and "Repeated".
- "Met_criteria" is initialized "FALSE". Then "which(metCriteria(pots))" picks the row numbers where the criteria are met. In these rows "Met_critaria" is set to "TRUE".
- "Repeated" is initialized "TRUE". It is set to "FALSE" in those rows where the corresponding date and ID occures for the last time.
Example:
> 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
>
Upvotes: 2
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