R: How to calculate mean for each row with missing values using dplyr

Question

I want to calculate means over several columns for each row in my dataframe containing missing values, and place results in a new column called \'means.\' Here\'s my datafra

Answer 1

Regarding the error in OP's code, we can use the concatenate function c to get those elements as a single vector and then do the mean as mean can take only a single argument.

df %>%
    rowwise() %>% 
    mutate(means = mean(c(A, B, C), na.rm = TRUE))
#     A     B     C    means 
#        
#1     3     0     9 4.000000
#2     4     6    NA 5.000000
#3     5     8     1 4.666667

---

Also, we can use rowMeans with transform

transform(df, means = rowMeans(df, na.rm = TRUE))
#  A B  C    means
#1 3 0  9 4.000000
#2 4 6 NA 5.000000
#3 5 8  1 4.666667

Or using data.table

library(data.table)
setDT(df)[, means := rowMeans(.SD, na.rm = TRUE)]