How do I change the "NA" string to actual NA for all columns in my Data?

Question

I have a dataset with 40 columns and 9000 rows, all of the columns contain at least one string "NA". I want to drop every row that has at least one "NA" but I need to change it to an actual NA value beforehand.

I cannot use the na.strings="" argument as I am getting my data using the opendatatoronto package, not read.csv.

I have also tried this code, which didn't work either. for(i in names(data)) (set(data, which(data[[i]] == "NA"), i, NA))

You may use `df1 <- type.convert(df, as.is = TRUE);df1 <- df1[complete.cases(df1),]` — akrun, Jan 29 '22 at 22:49

score 1 · Accepted Answer · answered Jan 29 '22 at 22:59

1

dplyr::na_if() should do the trick:

df <- tibble( x = c('A', 'NA', 'C'), 
        y = c('D', 'E', 'NA'), 
        z = c('NA', 'NA', 'I' ))

na_if(df, 'NA')

answered Jan 29 '22 at 22:59

tivd

750
3
17

score 1 · Answer 2 · answered Jan 29 '22 at 23:01

1

What about

dat[dat == 'NA'] <- NA

answered Jan 29 '22 at 23:01

Anil

1,097
7
20

How do I change the "NA" string to actual NA for all columns in my Data?

2 Answers2