On 14/09/13 06:48, Chinmay Patil wrote:
I didn't mean changes in data.table's interface but the way data.table works in
itself compared to normal data frames. I know there are valid reasons for
structuring data.table's interface the way it is but not all users get it
immediately.
The bottom line in my mind is that even if base syntax was sped up
(assignment to an unnamed data.frame needn't copy the whole data.frame
for example), I would still move from
subset()/transform()/with()/DF[i,j]<-value syntax, to i,j and by inside
[...] with .SD,.I,.N and := in j. I can do things with that syntax
that I need to do which aren't always so easy with base syntax (like
adding columns by reference by group).
And base R syntax is indeed being sped up by pqR, Renjin, Riposte, TERR,
CXXR, fastr which may feed into GNU R. Once that is mature and the dust
has settled, I would still move from data.frame to data.table on each of
them. Maybe we should market the things that data.table does that base
R doesn't. Rather than speed differences.
As for data.table, I am not complaining, just saying what other users
complaints I have heard of.
I personally love data.table and am willing to put the effort to learn best
ways to use it while most users aren't.
Great. data.table is for people like you.
So we'll keep the default fread'ing of "T" and "F" as logicals then for
consistency with read.csv.
And I still hope to produce a drop-in replacement for read.csv which
returns a data.frame but uses fread under the hood. That will speed up
existing code, but users can use the extra features of fread if they
want, too.
Matthew
Chinmay
On 14 Sep, 2013, at 1:29 PM, Steve Lianoglou <[email protected]> wrote:
Thanks for the quick response.
As for the "learning curve" stuff -- no real comment there, but:
For eg. I recently heard complains about data.table itself from due to
changes in interface
Could you provide some concrete examples about which changes have
stumped users? Perhaps we can learn from these critiques. I had
thought we were pretty good about discussing any (breaking) changes on
list, but I'd be interested to see where this has failed so it might
perhaps be avoided in the future.
and learning curve that data.table comes with... I hear
similar complaints about some packages like ggplot2, plyr..
Even though all these are great packages.. people don't like radical changes
to interfaces as it makes refactoring older code even more painful.
Still curious to hear what radical changes have come down the pipe.
Thanks for taking the time to comment.
Cheers,
-steve
--
Steve Lianoglou
Computational Biologist
Bioinformatics and Computational Biology
Genentech
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