Determine the number of NA values in a column

Question

I want to count the number of NA values in a data frame column. Say my data frame is called df, and the name of the column I am considering is

Answer 1

You're over-thinking the problem:

sum(is.na(df$col))

Answer 2

If you are looking for NA counts for each column in a dataframe then:

na_count <-sapply(x, function(y) sum(length(which(is.na(y)))))

should give you a list with the counts for each column.

na_count <- data.frame(na_count)

Should output the data nicely in a dataframe like:

----------------------
| row.names | na_count
------------------------
| column_1  | count

Answer 3

This form, slightly changed from Kevin Ogoros's one:

na_count <-function (x) sapply(x, function(y) sum(is.na(y)))

returns NA counts as named int array

Answer 4

sapply(name of the data, function(x) sum(is.na(x)))

Answer 5

A tidyverse way to count the number of nulls in every column of a dataframe:

library(tidyverse)
library(purrr)

df %>%
    map_df(function(x) sum(is.na(x))) %>%
    gather(feature, num_nulls) %>%
    print(n = 100)

Answer 6

If you are looking to count the number of NAs in the entire dataframe you could also use

sum(is.na(df))