使用列名向量在循环中重新编码data.table值

Question

I have a large data table that contains some categorical variables, where missing values have been coded as blank strings. I would like to recode them to NA.

I have a vector storing the names of the categorical variables:

categorical_variables = c("v3", etc.

The vector is definitely set up correctly - I have successfully used it to loop through plots of each column. However when I try to recode using this...

for (v in categorical_variables) myDataTable[get(v)=="",get(v):=NA]

...I get the following error:

 Error in get(v) : object 'v3' not found

Yet this works OK:

myDataTable[v3=="",v3:=NA]

And this also works OK:

myDataTable[get("v3")=="",get("v3")]

So it's when I try to do the assignment using get() combined with := it throws up the error. What am I doing wrong?

The data.table is very large (hence my preference for using data.table), so ideally I don't want to convert to data.frame and use a base R approach. I feel like this should be a very straightforward procedure in data.table, but I've really struggled to find anything conclusive in the documentation, on Google, or on here! Is this a bug or am I missing something obvious?

Answer 1

We can use set . According to ?set , it is very fast as the overhead of [.data.table is avoided

library(data.table)
for (v in categorical_variables){
   set(myDataTable, i=which(myDataTable[[v]]==""), j=v, value=NA)
 }

However, this can be avoided while reading itself, as fread has the na.strings option (just like read.csv/read.table ). We can specify the characters that needs to be read as NA ie if we have "" and $ to read as NA ,

myDataTable <- fread("yourfile.csv", na.strings=c("", "$"))

data

myDataTable <- data.table(v3=c(letters[1:3], ''), 
        v5 = 1:4, v7 = c('', '', letters[1:2]))