I have a question similar to this one, but my dataset is a bit bigger: 50 columns with 1 column as UID and other columns carrying either TRUE
or NA
Try this code:
df <- data.frame(
id = c(rep(1:19), NA),
x1 = sample(c(NA, TRUE), 20, replace = TRUE),
x2 = sample(c(NA, TRUE), 20, replace = TRUE)
)
replace(df, is.na(df), FALSE)
UPDATED for an another solution.
df2 <- df <- data.frame(
id = c(rep(1:19), NA),
x1 = sample(c(NA, TRUE), 20, replace = TRUE),
x2 = sample(c(NA, TRUE), 20, replace = TRUE)
)
df2[names(df) == "id"] <- FALSE
df2[names(df) != "id"] <- TRUE
replace(df, is.na(df) & df2, FALSE)