I am importing a csv that has a single column which contains very long integers (for example: 2121020101132507598)
a<-read.csv(\'temp.csv\',as.is=T
The maximum value of a 32-bit signed integer is 2,147,483,647. Your numbers are much larger.
Try importing them as floating point values instead.
There4 are a few caveats to be aware of when dealing with floating point arithmetic in R or any other language:
http://blog.revolutionanalytics.com/2009/11/floatingpoint-errors-explained.html
http://blog.revolutionanalytics.com/2009/03/when-is-a-zero-not-a-zero.html
http://floating-point-gui.de/basic/
As others have noted, you can't represent integers that large. But R isn't reading those values into integers, it's reading them into double precision numerics.
Double precision can only represent numbers to ~16 places accurately, which is why you see your numbers rounded after 16 places. See the gmp, Rmpfr, and int64 packages for potential solutions. Though I don't see a function to read from a file in any of them, maybe you could cook something up by looking at their sources.
UPDATE:
Here's how you can get your file into an int64
object:
# This assumes your numbers are the only column in the file
# Read them in however, just ensure they're read in as character
a <- scan("temp.csv", what="")
ia <- as.int64(a)
R's maximum intger value is about 2E9. As @Joshua mentions in another answer, one of the potential solutions is the int64 package.
Import the values as character instead. Then convert to type int64.
require(int64)
a <- read.csv('temp.csv', colClasses = 'character', header=FALSE)[[1]]
a <- as.int64(a)
print(a)
[1] 4031320121153001444 4113020071082679601 4073020091116779570
[4] 2081720101128577687 4041720081087539887 4011120071074301496
[7] 4021520051054304372 4082520061068996911 4082620101129165548
You simply cannot represent integers that big. See
.Machine
which on my box has
$integer.max
[1] 2147483647