[R] get is.na & !is.na count of various combinations of columns

arun smartpink111 at yahoo.com
Wed Mar 19 05:59:30 CET 2014


If you want to identify the combination of columns:

names1 <-  unlist(lapply(seq(length(vec1)-1),function(i) {x1 <- as.data.frame(combn(vec1,i),stringsAsFactors=FALSE); unlist(lapply(x1, function(x) {indx <- vec1 %in% x; paste(paste(paste0("!is.na","(", vec1[!indx],")"),collapse=" & "), paste(paste0("is.na","(", vec1[indx],")"),collapse= " & "), sep= " & ") }))}),use.names=FALSE)


res1 <- unlist(res,recursive=FALSE)
 names(res1) <- names1

res1
 length(res1)
#[1] 30
res1[30]
#$`!is.na(Poster) & is.na(Records) & is.na(MWBW) & is.na(OT) & is.na(CL)`
#   CaseID Structure Poster Records MWBW OT CL
#6 1605951      prop      1      NA   NA NA NA
res2 <- res1[sapply(res1,nrow)!=0]
res2[4]
#$`!is.na(Poster) & !is.na(Records) & is.na(MWBW) & is.na(OT) & is.na(CL)`
#   CaseID Structure Poster Records MWBW OT CL
#1 1605928      corp      1       1   NA NA NA
#2 1605943      corp      1       1   NA NA NA

Hope this helps.


A.K.




On , arun <smartpink111 at yahoo.com> wrote:
Hi,
May be this helps:
res <-  lapply(seq(length(vec1)-1),function(i) {x1 <- as.data.frame(combn(vec1,i),stringsAsFactors=FALSE); lapply(x1, function(x) {indx <- vec1 %in% x; nisna <- paste(paste0("!is.na","(", vec1[!indx],")"),collapse=" & ");isna <- paste(paste0("is.na","(", vec1[indx],")"),collapse= " & ");subset(mydatatest, eval(parse(text=nisna)) & eval(parse(text=isna)))})})

A.K.





On Tuesday, March 18, 2014 11:45 PM, bcrombie <bcrombie at utk.edu> wrote:
I'm trying to count the number of combinations of columns containing data &
not containing data as described below.  I"m not sure how to do this in R
and need some help.

#get TRUE/FALSE count of various combinations of columns per CaseID or per
Structure
mydatatest <- data.frame (CaseID = c("1605928", "1605943", "1605945",
"1605947", "1605949", "1605951"),
                      Structure = c("corp", "corp", "prop", "LLC", "LLC",
"prop"),
                      Poster = c(1, 1, 1, NA, NA, 1),
                      Records = c(1, 1, 1, 1, 1, NA),
                      MWBW = c(NA, NA, 495.10, NA, NA, NA),
                      OT = c(NA, NA, NA, NA, 411.25, NA),
                      CL = c(NA, NA, NA, 13.52, NA, NA))

combo1 <- subset(mydatatest, !is.na(Poster & Records & MWBW & OT & CL))
combo2 <- subset(mydatatest, !is.na(Poster & Records & MWBW & OT) &
is.na(CL))
combo3 <- subset(mydatatest, !is.na(Poster & Records & MWBW) & is.na(OT &
CL))
combo4 <- subset(mydatatest, !is.na(Poster & Records) & is.na(MWBW & OT &
CL))
combo5 <- subset(mydatatest, !is.na(Poster) & is.na(Records & MWBW & OT &
CL))
combo6 <- subset(mydatatest, !is.na(Records) & is.na(Poster & MWBW & OT &
CL))
combo7 <- subset(mydatatest, !is.na(MWBW) & is.na(Poster & Records & OT &
CL))
combo8 <- subset(mydatatest, !is.na(OT) & is.na(Poster & Records & MWBW &
CL))
combo9 <- subset(mydatatest, !is.na(CL) & is.na(Poster & Records & MWBW &
OT))
etc.



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