Removing missing values from merged categorical variables in R-CodePudding

In response to my previous question here:

Merging binary variables in R to a new variable

I used the following code to merge categorical variables and it worked:

koratest<-koratest%>%
      rowwise() %>%
      mutate(
          CVD = min(ptmi,ptschl,pthyact, ptap )
      ) %>%
      ungroup()

What to do if there is missing values in any of the values to be merged. I want missing values to be labelled as 1 but if there is 0 with missing value, i want cvd variable to have value of 1. For example:

 Stroke  MI  BP  CVD
 0       1    1   0
 1       NA   NA  1
 0       NA   1   0

How should i edit the above mentioned code in this case?

CodePudding user response：

You could first replace the NA with 1 and then apply the same function:

df[is.na(df)] <- 1
df$CVD <- apply(df,1, function(x) !any(0 %in% x))   0
df

Output:

  Stroke MI BP CVD
1      0  1  1   0
2      1  1  1   1
3      0  1  1   0

CodePudding user response：

replace them with 1.

replace(dat, is.na(dat), 1) |> {\(.) transform(., CVD= (rowSums(.) == 3))}()
#   Stroke MI BP CVD
# 1      0  1  1   0
# 2      1  1  1   1
# 3      0  1  1   0

Data:

dat <- structure(list(Stroke = c(0L, 1L, 0L), MI = c(1L, NA, NA), BP = c(1L, 
NA, 1L)), class = "data.frame", row.names = c(NA, -3L))