How to plot the density curve of a vector containing missing values in R?

Question

I have a data set with some NA values (missing values).

Because I need to plot some density curves from this data, I've created the following function:

plotDistribution = function (x) {
    N = length(x)
    hist( x,col = "light blue",
          probability = TRUE)
    lines(density(x), col = "red", lwd = 3)
    rug(x)
}

It works just fine if x has no missing values but because my data do contain missing values I'm getting the following message: Error in density.default(x) : 'x' contains missing values .

My question is: how to plot the density curve of the non-missing values in a data set? How can I ignore the NA and plot the curve as if they don't exist?

Answer 1

You can just take the non missing values of x in the function, such as:

plotDistribution = function (x) {
  NoMissing <- x[!is.na(x)]
  N = length(NoMissing)
  hist( NoMissing,col = "light blue",
        probability = TRUE)
  lines(density(NoMissing), col = "red", lwd = 3)
  rug(NoMissing)
}

Answer 2

It should work just adding na.omit()

plotDistribution = function (x) {
  N = length(x)
  x <- na.omit(x)
  hist( x,col = "light blue",
        probability = TRUE)
  lines(density(x), col = "red", lwd = 3)
  rug(x)
  print(N-length(x))
}

This function can hide data bugs in many cases, so i added a line that print the number of ommited values.