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rdata.tablefwrite

Disable Exponential Notation when printing with fwrite r

I have run into an issue where even when I disable exponential notation, fwrite prints the number in exponential notation. An example:

library(data.table)
options(scipen = 999)
testint = c(500000)

Before I print, r behaves and does not print in exponential notation:

print(testint)
[1] 500000
print(list(testint)
[[1]]
[1] 500000

But when I do:

fwrite(list(testint), "output")

The content of the file is 5e+05. I suspect this issue may specifically be with fwrite, as when I do:

write(testint, "output1")

The content of the output file is 500000.

Is there any way to prevent fwrite from doing this? I could switch to using write, but there is a massive speed difference between them and I am writing a lot of data, so there would be a significant performance impact that I would like to avoid if possible. Thanks!

Edit: if anyone is interested, there is an existing open github issue here that I found after I asked the question!

Solution

  • If you look at the source code of fwrite() function it passes the values your values straight to internal C function:

    > fwrite
function (x, file = "", append = FALSE, quote = "auto", sep = ",",
    sep2 = c("", "|", ""), eol = if (.Platform$OS.type == "windows") "\r\n" else "\n",
    na = "", dec = ".", row.names = FALSE, col.names = TRUE,
    qmethod = c("double", "escape"), logicalAsInt = FALSE, dateTimeAs = c("ISO",
        "squash", "epoch", "write.csv"), buffMB = 8, nThread = getDTthreads(),
    showProgress = getOption("datatable.showProgress"), verbose = getOption("datatable.verbose"))
{
...
    .Call(Cwritefile, x, file, sep, sep2, eol, na, dec, quote,
        qmethod == "escape", append, row.names, col.names, logicalAsInt,
        dateTimeAs, buffMB, nThread, showProgress, verbose)
    invisible()
}

    If you look at the source code of the function that is called: https://github.com/Rdatatable/data.table/blob/master/src/fwrite.c you will notice that they do not check for any environment set in R and use significant notation for large enough values. One can change this source the way you like, build own dynamic library and call it from R. The other option would be to use some standard R writing functions (though I suspect you like the performance of data.table package functions).