R - How to combine multiple boolean columns (don't know how many) into one column-CodePudding

I have a dataset looks like this:

df1 <- data.frame(
  date = c(20200101, 20200102, 20200103,20200104,20200105,20200106), 
  z_score = c(TRUE, TRUE, TRUE, FALSE, FALSE, TRUE), 
  mad_score = c(FALSE, TRUE, TRUE, TRUE, TRUE, TRUE),
  history_error = c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE),
  manual = c(TRUE, TRUE, TRUE, TRUE, FALSE, TRUE)
)

The result needs to like:

      date final_result
1 20200101        FALSE
2 20200102         TRUE
3 20200103         TRUE
4 20200104        FALSE
5 20200105        FALSE
6 20200106         TRUE

I can do that by un-pivot to long form and summarize the boolean columns together as:

df1_result <- df1 %>% 
  pivot_longer(!date, names_to = "conditions", values_to = "T_or_F") %>% 
  group_by(date) %>% 
  summarise(T_or_F = as.logical(prod(T_or_F)))

I feel there must be a simpler way to do it. I searched the solution in the forum and found many 1-liner for similar question. I just can't replicate those elegant 1-liner to my issue.

CodePudding user response：

Here's a one liner that uses only base R

data.frame(df1[1], final_result = apply(df1[-1], 1, \(x) sum(x) == 4))
#>       date final_result
#> 1 20200101        FALSE
#> 2 20200102         TRUE
#> 3 20200103         TRUE
#> 4 20200104        FALSE
#> 5 20200105        FALSE
#> 6 20200106         TRUE

CodePudding user response：

In tidyverse, we can use if_all

library(dplyr)
df1 %>%
   transmute(date, result = if_all(where(is.logical)))

-output

      date result
1 20200101  FALSE
2 20200102   TRUE
3 20200103   TRUE
4 20200104  FALSE
5 20200105  FALSE
6 20200106   TRUE

CodePudding user response：

Not a one liner, but we can make the calculation using rowSums, then select the desired columns. No need to pivot to long form.

library(tidyverse)

df1 %>%
  mutate(final_result = rowSums(across(where(is.logical))) == 4) %>%
  select(date, final_result)

Output

      date final_result
1 20200101        FALSE
2 20200102         TRUE
3 20200103         TRUE
4 20200104        FALSE
5 20200105        FALSE
6 20200106         TRUE