R won't recognize missing data

Question

I have a dataset with multiple columns. In some columns all values are missing, in other columns only a few values. When importing to R, the missing values are only shown as empty cells and not as NA. This results in the problem that when I want to remove NA values with the na.omit() function nothing happens. How should I handle this problem?

related: https://stackoverflow.com/questions/24172111/change-the-blank-cells-to-na — VYago, Mar 28 '22 at 16:54

score 1 · Accepted Answer · answered Mar 28 '22 at 17:16

1

You could replace all the empty values with NA by using the following code:

library(dplyr)
your_data_with_NA <- your_data %>% 
  mutate_all(na_if, "")

answered Mar 28 '22 at 17:16

Quinten

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score 1 · Answer 2 · answered Mar 28 '22 at 17:22

The easiest is often to fix this when importing your data. Most functions for importing data has some argument to specify which values should be interpreted as NA, for example:

read.csv and the like: na.strings
readr::read_csv and the like: na
readxl::read_excel and the like: na

Just set this argument to "", " " or to any value that is not interpreted as NA by R.

If this is not an option for you, you can replace the blank values with NA using:

library(dplyr)

df %>% 
  mutate(
    across(
      everything(),
      ~na_if(.x, "")
    )
  )

Note that mutate(across(everything())) has superseeded mutate_all but does the same.

Data

df <- mtcars %>% head()

df[1, 1] <- ""

R won't recognize missing data

2 Answers2

Data