使用 summarize_if 按 dplyr 中的每一列计算非 NA 值

Question

I want to count the number of non-missing rows in each column that meets a criteria. Below is the code I currently have.

data(mtcars)

mtcars %>% 
  summarize_if(is.numeric, sum(!is.na()))

Answer 1

Please be aware that summarise_if has been superseded, so it's recommended to use across and where instead. However, your original code was close, you just needed a tilde ( ~ ).

The dataset mtcars has no missing values, so I used airquality instead.

library(tidyverse)
data(airquality)

airquality %>% 
  summarise(across(where(is.numeric), ~ sum(!is.na(.x))))
#>   Ozone Solar.R Wind Temp Month Day
#> 1   116     146  153  153   153 153

airquality %>% 
  summarise_if(is.numeric, ~ sum(!is.na(.x)))
#>   Ozone Solar.R Wind Temp Month Day
#> 1   116     146  153  153   153 153