Sum/return NA when all values are NA-CodePudding

I'm trying to run a function on columns that have NA observations. When all observations are NA I would like it to return NA, but when only a fraction of rows has it, just apply na.rm=T. I've seen a few posts showing how to do this (link_1, link_2, link_3), but none of them seem to work for my function and I'm not sure where I'm going wrong.

# data frame
species_1<- c(NA, 10, 40)
species_2<- c(NA, NA, 30)
species_3<- c(NA, NA, NA)
group<- c(1, 1, 1)

df<- data.frame(species_1, species_2, species_3, group)

# function argument
y_true_test<- c(30, 20, 20) 

# function
estimate = function(df, y_true, na.rm=T) {
  
  if (all(is.na(df))) df[NA_integer_] else
  
  sqrt(colSums((t(t(df) - y_true_test))^2, na.rm=T) / 3) / y_true_test * 100
  
}

# run
final<- df %>%
  group_by(group) %>%
  group_modify( ~ as.data.frame.list(estimate(., y_true_test))) #species 3 returns '0' when it should be NA

Any help would be greatly appreciated.

CodePudding user response：

The function was checking the NA on the whole dataset columns instead it should be by each column. Here, is an option with across

library(dplyr)
names(y_true_test) <- grep("species", names(df), value = TRUE)
df %>%
   group_by(group) %>% 
   summarise(across(everything(), ~ if(all(is.na(.x))) NA_real_ else
     sqrt(sum((.x - y_true_test)^2, na.rm = TRUE)/n())/
                (y_true_test[cur_column()]) * 100), .groups = 'drop')

-output

# A tibble: 1 × 4
  group species_1 species_2 species_3
  <dbl>     <dbl>     <dbl>     <dbl>
1     1      43.0      28.9        NA

If we want to modify the OP's function

estimate <- function(df, y_true, narm=TRUE) {
  
  i1 <- colSums(is.na(df)) == nrow(df)
  
  
   out <- sqrt(colSums((t(t(df) - y_true_test))^2,
        na.rm= narm) / 3) / y_true_test * 100
   out[i1] <- NA
   out
  
}

-testing

> df %>%
    group_by(group) %>%
    group_modify( ~ as.data.frame.list(estimate(., 
          y_true_test))) 
# A tibble: 1 × 4
# Groups:   group [1]
  group species_1 species_2 species_3
  <dbl>     <dbl>     <dbl>     <dbl>
1     1      43.0      28.9        NA