allMissing: Identifies missing rows or columns in a data frame or matrix
In Smisc: Sego Miscellaneous

Description Usage Arguments Value Author(s) See Also Examples

Indicates which rows or columns in a data frame or matrix are completely missing (all values are NA's).

1	allMissing(dframe, byRow = TRUE)

`dframe`	A data frame or a matrix
`byRow`	`= TRUE` will identify rows that have all missing values. `= FALSE` identifies entire missing columns

A logical vector that is true if all the elements in the corresponding row (or column) are NA's.

Landon Sego

complete.cases

# Start off with a simple data frame that has a few missing values
d1 <- data.frame(x=c(3,4,NA,1,10,NA), y=c(NA,"b","c","d","e",NA))
d1

# Identify rows were the entire row is missing
allMissing(d1)

# Only removes rows where all the values are missing
d1[!allMissing(d1),]

# All missing can also be used to identify if any of the
# columns are 'all missing'
d2 <- data.frame(x=c(rnorm(3), NA, rnorm(6)), y=rep(NA,10), z=letters[1:10])
d2

# Look for columns that are all missing
allMissing(d2, byRow=FALSE)

# Remove columns where all the values are missing
d2[,!allMissing(d2, byRow = FALSE)]