NA is being counted as zero in mutate-CodePudding

I'm having a problem where I want to mutate two variables with values 0, 1 and NA into a new variable with the sum of 0 and 1, however, R in my case counts NA as 0 or return only NA. Are there an easy fix to this, to exclude the NA?

I am using an R-textbook that does not adress my specific problem.

Code I have tried:

(1)
library(tidyverse)

df <- df |> 
  mutate((naked_man = naked_fj   naked_naked), na.rm = TRUE)

Returns all OBS as NA

Data:

naked_fj	naked_naked	naked_man (problem VAR)
0	0	NA
1	0	NA
NA	1	NA
0	NA	NA

CodePudding user response：

you are just setting it up incorrectly for the mutate function. You can also use the tidyr::drop_na to remove the NA values in the data frame.

library(tidyverse)

df <- data.frame(naked_fj = c(0,1, NA, 0),
                 naked_naked = c(0, 0, 1, NA))
                 
df <- df |>
  mutate(naked_man = naked_fj   naked_naked) %>% 
  drop_na()

RESULT:

  naked_fj naked_naked naked_man
1        0           0         0
2        1           0         1

CodePudding user response：

To sum across columns excluding the NA, one implementation of your code in dplyr is to use rowwise :

df |> 
  rowwise() |>
  mutate(naked_man = sum(c(naked_fj, naked_naked), na.rm = TRUE))

#          naked_fj naked_naked naked_man
#          <dbl>       <dbl>     <dbl>
# 1        0           0         0
# 2        1           0         1
# 3       NA           1         1
# 4        0          NA         0

But if not needing to use dplyr, base R may be easier:

df$naked_man <- rowSums(df, na.rm = TRUE)

Data:

df <- read.table(text = "naked_fj   naked_naked naked_man
               0    0   NA
               1    0   NA
               NA   1   NA
               0    NA NA", header = TRUE)

df <- df[,-3]
df[] <- lapply(df[], as.numeric)