r - Dropping all NAs in a dataframe and then upshifting the cleaned columns

Question

I found the script below for cleaning NAs and left-shifting rows. Here's the discussion: Dropping all left NAs in a dataframe and left shifting the cleaned rows

for (i in 1:nrow(dat)) {

if (is.na(dat[i,1])==TRUE) {
    dat1 <- dat[i, min(which(!is.na(dat[i,]))):length(dat[i,])]
    dat[i,]  <- data.frame( dat1, t(rep(NA, ncol(dat)-length(dat1))) )
}

}

dat

I'd like to clean a varying number of NAs from the top of columns and then upshift the cleaned columns. Is there any chance someone could help me modify the above script for that purpose?

Why do you want to do this? The data values will get mixed up. — Rich Scriven, Nov 04 '14 at 03:20
@Hedgehog: when you say 'upshifting', do you mean "I only want rows that don't contain any NA's"? — Alex Woolford, Nov 04 '14 at 03:39

score 0 · Accepted Answer · answered Nov 04 '14 at 04:20

Like this?

dat <- as.data.frame(rbind(c(NA,NA,1,3,5,NA,NA,NA), c(NA,1:3,6:8,NA), c(1:7,NA)))
dat
#   V1 V2 V3 V4 V5 V6 V7 V8
# 1 NA NA  1  3  5 NA NA NA
# 2 NA  1  2  3  6  7  8 NA
# 3  1  2  3  4  5  6  7 NA

dat[] <- apply(dat, 2, function(x) `length<-`(na.omit(x), length(x)))
dat
#   V1 V2 V3 V4 V5 V6 V7 V8
# 1  1  1  1  3  5  7  8 NA
# 2 NA  2  2  3  6  6  7 NA
# 3 NA NA  3  4  5 NA NA NA

r - Dropping all NAs in a dataframe and then upshifting the cleaned columns

1 Answers1