Good.  Now committed in v1.8.11 (rev 966).  Also drop and select is done.

o fread's drop, select and NULL in colClasses are implemented. To drop or select columns by name
     or by number. See examples in ?fread.

o fread now detects T,F,True,False,TRUE and FALSE as type logical, consistent with read.csv.

I pasted the new examples from ?fread to this answer as well:
http://stackoverflow.com/a/18702011/403310

Hope this covers everything in this area, but please shout if anyone can think of anything further.

Matthew


On 15/09/13 22:42, Eduard Antonyan wrote:

+1 for T and F, but definitely not because it's that way in read.csv (which imo is not a good reason), but rather because those are commonly used substitutes for TRUE and FALSE.

On Sep 14, 2013 5:29 AM, "Arunkumar Srinivasan" <[email protected] <mailto:[email protected]>> wrote:

    Matthew,

    +1 for retaining T and F like read.csv.
    +1 for the dropins() feature as well.

    Arun

    On Saturday, September 14, 2013 at 11:53 AM, Matthew Dowle wrote:

    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] <mailto:[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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