R: how to total the number of NA in each col of data.frame

Question

To calculate the number of NAs in the entire data.frame, I can use sum(is.na(df), however, how can I count the number of NA in each column of a big data.frame? I tried apply(df, 2, function (x) sum(is.na(df$x)) but that didn't seem to work.

Answer 1

You could try:

colSums(is.na(df))
#  V1 V2 V3 V4 V5 
#   2  4  2  4  4 

data

set.seed(42)
df <- as.data.frame(matrix(sample(c(NA,0:4), 5*20,replace=TRUE), ncol=5))

Answer 2

With dplyr...

df %>%
  summarise_all(funs(sum(is.na(.))))

or using the purrr library

map(df, ~sum(is.na(.)))

Answer 3

You can use sapply :

sapply(X = df, FUN = function(x) sum(is.na(x)))

Answer 4

Since the dplyr::summarise_all function has been superseded by using across inside the original function and dplyr::funs has been deprecated, the current tidyverse approach would probably be something like:

df %>% 
  summarise(across(everything(), ~ sum(is.na(.x))))

Answer 5

To maintain the names of each column, use this variation (substitute name of dataframe for df in example):

apply(is.na(df), 2, sum)

Answer 6

You could try the following functions

1. Using colSums()

   colSums(is.na(df))

2. Using apply()

   apply(df, 2, function(x) {sum(is.na(x))})

3. Using a function

   sum.na <- function (x) { sum(is.na(x)) }

   print(sum.na(df))

4. Using lapply()

   lapply(df, function(x) sum(is.na(x)))

5. Using sapply()

   lapply(df, function(x) sum(is.na(x)))