如何根据每行中一些变量的单独平均值创建一个新变量？

Question

I have the following dataframe:

I want to the following in R:

• Create a new variable called 'Z' and bind it to my dataframe
• This should be the mean of each row
• If some variable is blank or contains an 'NA' then it should not get counted for the mean.

Here is what my desired output would look like:

Desired output in R:

Here is what I have tried doing:

I have tried to create a for loop which loops through each row to count number of non-blank variables, then it sums up all 3 variables and divides by the number of non-blank variables. Th problem is, I have to do this same task for 9 variables (in a dataframe which contains 50 variables) and that would mean a repetitive code and if blocks for 9 variables.

Is there a way around it?

Answer 1

The apply function in base R allows to loop over rows of data.frames. See ?apply for more info. The mean function has an na.rm option to automatically deal with NA entries.

x <- data.frame(
  id = c("A", "B"),
  A = c(5, 2),
  B = c(NA, 5),
  C = c(NA, 2)
)

x$Z <- apply(x[2:4], 1, function(x) { mean(x, na.rm = TRUE) })