I’m trying to count the number of NA values in each of 2 columns.

The code below works.

temp2 %>%
  select(c18basic, c18ipug) %>%
  summarise_all(funs(sum(is.na(.))))

But I get this warning:

Warning message:
`funs()` was deprecated in dplyr 0.8.0.
Please use a list of either functions or lambdas: 

  # Simple named list: 
  list(mean = mean, median = median)

  # Auto named with `tibble::lst()`: 
  tibble::lst(mean, median)

  # Using lambdas
  list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))

How can I rewrite my summarise_all line using each of the above techniques: Simple list and Auto named list? Without using summarise_all as it seems to have been superseded.

Thanks.

Note: I find TidyVerse documentation very difficult to understand. If someone can point me to a resource that could help me figure out these things on my own, I’d really appreciate it. Thank you in advance.

Note: I figured out how to do it using Lambda:

temp2 %>%
  select(c18basic, c18ipug) %>%
  summarise(across(everything(), ~ sum(is.na(.x))))

>Solution :

Like this?

   dplyr::summarize_all(list(sum= ~sum(is.na(.x), na.rm = T)))

Btw the select() is not necessary, you could write

temp2 %>%
  summarise(across(c(c18basic,c18ipug), ~ sum(is.na(.x))))

Ex.

library(dplyr)
mtcars[1,1] <- NA
mtcars %>% 
  summarise(across(c(mpg ,cyl), list(sum= ~sum(is.na(.x), na.rm = T))))

Results in

mpg_sum cyl_sum
    1       0

I think you get the idea and see how easy the syntax is, when using more functions, e.g.

mtcars[1,1] <- NA
mtcars %>%
  summarise(across(c(mpg, cyl), list(
    Mean = ~ mean(.x, na.rm = T),
    SD = ~ sd(.x, na.rm = T),
    Min = ~ min(.x, na.rm = T),
    Max = ~ max(.x, na.rm = T),
    Obs. = ~ sum(!is.na(.))
  )))