Randomly assigning values to missing data

[claybaugh]

How can I randomly assign a given number of 1s and 2s to cells with missing data within a vector? I know many 1s and 2s I need (but need to randomly assign them) and I have marked cells with missing data as NA.

Thanks.

[FJCC]

You can use the sample() function to generate a random set of 1s and 2s of a given length.

set.seed(34843)

#Make a vector with some NAs
x <- sample(c(10:13, NA), 20, replace = TRUE)

x
#>  [1] 13 12 13 13 11 NA 11 11 10 NA 13 NA 10 NA 11 11 12 12 12 11
y <- sum(is.na(x)) #count the NAs

#replace the NAs with 1 or 2
x[is.na(x)] <- sample(c(1,2), y, replace = TRUE)
x
#>  [1] 13 12 13 13 11  2 11 11 10  1 13  1 10  2 11 11 12 12 12 11

^{Created on 2019-03-20 by the reprex package (v0.2.1)}

[andresrcs]

With this information, the only thing that comes to my mind is sampling with probabilities, to control the amounts of 1s and 2s.

sample(1:2, 10, replace = TRUE, prob = c(0.3, 0.7))
#>  [1] 2 2 1 2 2 2 2 1 2 2

Could you please turn this into a self-contained REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

If you've never heard of a reprex before, you might want to start by reading this FAQ:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[andresrcs]

Another solution controlling the exact number of 1s and 2s

set.seed(34843)
x <- sample(c(10:13, NA), 20, replace = TRUE) # Made up data with NAs
num_na <- sum(is.na(x)) # Number of NA values
num_na
#> [1] 4
num_1 = 1 # Defining the number of 1s and 2s
num_2 = num_na - num_1
x[is.na(x)] <- sample(c(rep(1,num_1), rep(2,num_2)), 4) # Replacing NA values
x
#>  [1] 13 12 13 13 11  2 11 11 10  2 13  1 10  2 11 11 12 12 12 11