[datatable-help] Force evaluation of first argument to [

[Matt Dowle]

Ha.  Yes we certainly don't hold back from making the messages as long 
and as helpful as possible.  If the code knows, or can know what exactly 
is wrong, it's a deliberate policy to put that info right there into the 
message. data.table is written by users; i.e. we wrote it for ourselves 
doing real jobs. I think that may be the root of that.  If any messages 
could more helpful,  those suggestions are very welcome.

Matt

On 12/02/14 17:58, John Laing wrote:
> Thanks, Matt! With a slight amendment that works great:
> for (x in c("foo", "bar", "qux")) set(fbq, which(is.na 
> <http://is.na>(fbq[[x]])), x, FALSE)
>
> Which highlights an opportunity to say that I really appreciate the 
> unusually helpful error messages in this package.
>
> -John
>
>
> On Wed, Feb 12, 2014 at 12:44 PM, Matt Dowle <mdowle at mdowle.plus.com 
> <mailto:mdowle at mdowle.plus.com>> wrote:
>
>
>     Hi John,
>
>     In examples like this I'd use set() and [[,  since it's a bit
>     easier to write but memory efficient too.
>
>     for (x in c("foo", "bar", "qux"))   set(fbq, is.na
>     <http://is.na>(fbq[[x]]), x, FALSE)           [untested]
>
>     A downside here is one repetition of the "fbq" symbol, but can
>     live with that.  If you have a large number of columns  (and I've
>     been surprised just how many columns some poeple have!) then
>     calling set() many times has lower overhead than DT[, :=],  see
>     ?set.   Note also that [[ is base R, doesn't copy the column and
>     often useful to use with data.table.
>
>     Or, use get() in either i or j rather than eval().
>
>     HTH, Matt
>
>
>
>     On 12/02/14 17:24, John Laing wrote:
>>     Let's say I merge together several data.tables such that I wind up
>>     with lots of NAs:
>>
>>     require(data.table)
>>     foo <- data.table(k=1:4, foo=TRUE, key="k")
>>     bar <- data.table(k=3:6, bar=TRUE, key="k")
>>     qux <- data.table(k=5:8, qux=TRUE, key="k")
>>     fbq <- merge(merge(foo, bar, all=TRUE), qux, all=TRUE)
>>     print(fbq)
>>     #    k  foo  bar  qux
>>     # 1: 1 TRUE   NA   NA
>>     # 2: 2 TRUE   NA   NA
>>     # 3: 3 TRUE TRUE   NA
>>     # 4: 4 TRUE TRUE   NA
>>     # 5: 5   NA TRUE TRUE
>>     # 6: 6   NA TRUE TRUE
>>     # 7: 7   NA   NA TRUE
>>     # 8: 8   NA   NA TRUE
>>
>>     I want to go through those columns and turn each NA into FALSE. I can
>>     do this by writing code for each column:
>>
>>     fbq.cp <- copy(fbq)
>>     fbq.cp[is.na <http://is.na>(foo), foo:=FALSE]
>>     fbq.cp[is.na <http://is.na>(bar), bar:=FALSE]
>>     fbq.cp[is.na <http://is.na>(qux), qux:=FALSE]
>>     print(fbq.cp)
>>     #    k   foo   bar   qux
>>     # 1: 1  TRUE FALSE FALSE
>>     # 2: 2  TRUE FALSE FALSE
>>     # 3: 3  TRUE  TRUE FALSE
>>     # 4: 4  TRUE  TRUE FALSE
>>     # 5: 5 FALSE  TRUE  TRUE
>>     # 6: 6 FALSE  TRUE  TRUE
>>     # 7: 7 FALSE FALSE  TRUE
>>     # 8: 8 FALSE FALSE  TRUE
>>
>>     But I can't figure out how to do it in a loop. More precisely, I
>>     can't
>>     figure out how to make the [ operator evaluate its first argument in
>>     the context of the data.table. All of these have no effect:
>>     for (x in c("foo", "bar", "qux")) fbq[is.na <http://is.na>(x),
>>     eval(x):=FALSE]
>>     for (x in c("foo", "bar", "qux")) fbq[is.na
>>     <http://is.na>(eval(x)), eval(x):=FALSE]
>>     for (x in c("foo", "bar", "qux")) fbq[eval(is.na
>>     <http://is.na>(x)), eval(x):=FALSE]
>>
>>     I'm running R 3.0.2 on Linux, data.table 1.8.10.
>>
>>     Thanks in advance,
>>     John
>>
>>
>>     _______________________________________________
>>     datatable-help mailing list
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>
>

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