Omit rows containing specific column of NA

Use is.na

DF <- data.frame(x = c(1, 2, 3), y = c(0, 10, NA), z=c(NA, 33, 22))
DF[!is.na(DF$y),]

Use 'subset'

DF <- data.frame(x = c(1, 2, 3), y = c(0, 10, NA), z=c(NA, 33, 22))
subset(DF, !is.na(y))

You could use the complete.cases function and put it into a function thusly:

DF <- data.frame(x = c(1, 2, 3), y = c(0, 10, NA), z=c(NA, 33, 22))

completeFun <- function(data, desiredCols) {
  completeVec <- complete.cases(data[, desiredCols])
  return(data[completeVec, ])
}

completeFun(DF, "y")
#   x  y  z
# 1 1  0 NA
# 2 2 10 33

completeFun(DF, c("y", "z"))
#   x  y  z
# 2 2 10 33

EDIT: Only return rows with no NAs

If you want to eliminate all rows with at least one NA in any column, just use the complete.cases function straight up:

DF[complete.cases(DF), ]
#   x  y  z
# 2 2 10 33

Or if completeFun is already ingrained in your workflow ;)

completeFun(DF, names(DF))

Hadley's tidyr just got this amazing function drop_na

library(tidyr)
DF %>% drop_na(y)
  x  y  z
1 1  0 NA
2 2 10 33