On Fri, Jan 20, 2017 at 6:09 PM, Murray Stokely wrote:
> The lack of 64 bit integer support causes lots of problems when dealing
> with certain types of data where the loss of precision from coercing to 53
> bits with double is unacceptable.
>
> Two packages were developed to deal with this: int6
Le vendredi 20 janvier 2017 à 18:59 +0100, Martin Maechler a écrit :
> > > > > > > > > > > > Milan Bouchet-Valat
> > > > > > on Thu, 19 Jan 2017 13:58:31 +0100 writes:
> > Hi all,
> > I know this issue has been discussed a few times in the past already,
> > but Martin Maechler suggested in a b
To summarise this thread, there are basically three ways of handling int64 in R:
* coerce to character
* coerce to double
* store in double
There is no ideal solution, and each have pros and cons that I've
attempted to summarise below.
## Coerce to character
This is the easiest approach if the
I'm not sure whether or not this is a bug, but I did isolate the line
where the error is thrown:
src/library/base/R/dataframe.R:1395.
https://github.com/wch/r-source/blob/01374c3c367fa12f555fd354f735a6e16e5bd98e/src/library/base/R/dataframe.R#L1395
The error is thrown because the line attempts to
On 21 January 2017 at 10:56, Hadley Wickham wrote:
| To summarise this thread, there are basically three ways of handling int64 in
R:
|
| * coerce to character
| * coerce to double
| * store in double
|
| ## Coerce to character
Serious performance loss.
| ## Coerce to double
Serious precisi
