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View Code? Open in Web Editor NEWR's data.table package extends data.frame:
Home Page: http://r-datatable.com
License: Mozilla Public License 2.0
R's data.table package extends data.frame:
Home Page: http://r-datatable.com
License: Mozilla Public License 2.0
Submitted by: Garrett See; Assigned to: Arun ; R-Forge link
This is with revision 1260. When order() is in i, it does not respect abs()
library(data.table)
data.table 1.9.3 For help type: help("data.table")
order(abs(c(1, -2, 3)))
[1] 1 2 3
data.table(x=c(1, -2, 3))[order(abs(x))]
x
1: -2
2: 1
3: 3
Submitted by: agstudy agstudy; Assigned to: Arun ; R-Forge link
Amazing but this
unique(data.table(NULL))
returns an error:
Error in duplicated.data.table(x, incomparables, tolerance, by, ...) :
invalid subscript type 'list'
should return NULL data.table.
Submitted by: shubh bansal; Assigned to: Arun ; R-Forge link
dt=data.table(a=character(0), b=numeric(0), key='a')
unique(dt)
# a b
#1: NA NA
Submitted by: Arun ; Assigned to: Arun ; R-Forge link
The title may not be appropriate (as I've not looked into the issue yet, just that it crashes the session or gives a warning occasionally):
Code on behalf of Zack:
library(data.table)
dt<-data.table(strip="Nov08",date=c("2006-08-01","2006-08-02","2006-08-03","2006-08-04","2006-08-07",
"2006-08-08","2006-08-09","2006-08-10","2006-08-11","2006-08-14"))
dt[,forward_date:=c(rep(NA,5),date),by='strip']
It crashes or gives error: Link
Submitted by: Michele Carriero; Assigned to: Arun ; R-Forge link
Given the following table dt:
dt<-data.table(id=1:5, var=letters[1:5])
If I need to retrieve programmatically a column I use eval(parse(text=variable))
. But when the variable, containing (part of) the column name to retrieve, is also named alike another column in the table I have two different outcomes:
id<-"va"
dt[, eval(parse(text=paste0(id,"r")))]
# [1] "a" "b" "c" "d" "e"
dt[, id2:=eval(parse(text=paste0(id,"r")))]
# Error in parse(text = paste0(id, "r")) : <text>:1:2: unexpected symbol
1: 1r
^
I thought that the above was not intended to be so. I would expect the same result (probably the second).
Submitted by: Anja Mirenska; Assigned to: Nobody; R-Forge link
By chance, I attempted to create a combination of "levels" without having converted the columns to factors. This throws an error which is okay. However, after that, no matter what I try to do with this data.table, I get the same error again and again. Here is an MWE:
library(data.table)
DT <- data.table(Feature1 = c("yes", "yes", "no", "no"),
Feature2 = c("yes", "yes", "yes", "no"),
Feature3 = c("no", "yes", "yes", "no"),
Var1 = c("yes", "no", "no", "yes"),
Var2 = c("yes", "no", "yes", "yes"))
setkey(DT, Feature1)
DT[CJ(levels(Feature1), levels(Feature2), levels(Feature3)),
list(Var1.count = .N)]
setkey(DT, Feature1)
At this point, I have to restart the R session to get rid of this error.
I'm using Windows 7 x64, R Version 3.0.3, data.table 1.9.2
Submitted by: Eduard Antonyan; Assigned to: Arun ; R-Forge link
I've been getting unpredictable behaviours when using joins and get together. Here's an example that results in an error (in my real-life example the situation is actually much worse, in that I don't get an error but get incorrect results instead - I wasn't able to replicate it in a small example and am hoping it's the same issue as the one below):
dt1 = data.table(a = 1:2, b = 1:2, key = 'a')
dt2 = data.table(a = 1:2, c = 2:1, key = 'a')
dt1[dt2, list(c, get('b'))]
#Error in rep(x[[i]], length.out = mn) :
# attempt to replicate an object of type 'builtin'
These all work though:
dt1[dt2, list(c, b)]
dt1[dt2, list(a, get('b'))]
dt1[dt2, list(b, get('b'))]
dt1[dt2][, list(c, get('b'))]
Submitted by: Christophe Dervieux; Assigned to: Arun ; R-Forge link
Hi,
I have updated data.table package to 1.9.2 recently from 1.8.10 and I found errors on my previous code.
See reproductible example below:
On 1.8.10 :
DT <- data.table(X = factor(2006:2012), Y = rep(1:7, 2))
DT[, Z := paste(X, .N, sep = " - "), by = list(X)][]
X Y Z
1: 2006 1 2006 - 2
2: 2007 2 2007 - 2
3: 2008 3 2008 - 2
4: 2009 4 2009 - 2
5: 2010 5 2010 - 2
6: 2011 6 2011 - 2
7: 2012 7 2012 - 2
8: 2006 1 2006 - 2
9: 2007 2 2007 - 2
10: 2008 3 2008 - 2
11: 2009 4 2009 - 2
12: 2010 5 2010 - 2
13: 2011 6 2011 - 2
14: 2012 7 2012 - 2
In column Z, I get the level of the factor column X
pasted with count '.N' as expected
However, in the 1.9.2, with same code :
DT<-data.table(X=factor(2006:2012),Y=rep(1:7,2))
DT[,Z:=paste(X,.N,sep=" - "),by=list(X)][]
X Y Z
1: 2006 1 1 - 2
2: 2007 2 2 - 2
3: 2008 3 3 - 2
4: 2009 4 4 - 2
5: 2010 5 5 - 2
6: 2011 6 6 - 2
7: 2012 7 7 - 2
8: 2006 1 1 - 2
9: 2007 2 2 - 2
10: 2008 3 3 - 2
11: 2009 4 4 - 2
12: 2010 5 5 - 2
13: 2011 6 6 - 2
14: 2012 7 7 - 2
as results, I do not get levels of factor column X but the numeric values associated with the level.
is this working normally? Why has it changed? Is that a bug?
I use this kind of procedure to make labels for ggplot
. All my previous code is not working anymore. It's kind of annoying.
Thanks
Christophe
Submitted by: David Slate; Assigned to: Nobody; R-Forge link
I hope the following log is self-explanatory. Either I am confused, or data.table_1.9.2 apparently gets mixed up about the correspondence between column names and columns:
Script started on Wed May 14 01:02:01 2014
1�]0;david@LC2430HD: �david@LC2430HD:$ date
Wed May 14 01:02:04 CDT 2014
1�]0;david@LC2430HD: �david@LC2430HD:$ uname -a
Linux LC2430HD 3.13.0-24-generic #47-Ubuntu SMP Fri May 2 23:30:00 UTC 2014 x86_64 x86_64 x86_64 GNU/Linux
1�]0;david@LC2430HD: �david@LC2430HD:$ cat dt-bug.r
options( echo = TRUE)
library( data.table)
sessionInfo()
DT <- data.table( x = 5, a = "blah", y = 8)
setkey( DT, a)
DT
DT[ J( "blah")]
DT[ J( "blah")]$y
DT[ J( "blah")]$y <- 3
DT
1�]0;david@LC2430HD: �david@LC2430HD:$
1�]0;david@LC2430HD: �david@LC2430HD:$ ./dt-bug.r
library( data.table)
sessionInfo()
R version 3.0.0 (2013-04-03)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] C
attached base packages:
[1] stats graphics grDevices utils datasets base
other attached packages:
[1] data.table_1.9.2
loaded via a namespace (and not attached):
[1] methods_3.0.0 plyr_1.8 reshape2_1.2.1 stringr_0.6
DT <- data.table( x = 5, a = "blah", y = 8)
setkey( DT, a)
DT
x a y
1: 5 blah 8
DT[ J( "blah")]
a x y
1: blah 5 8
DT[ J( "blah")]$y
[1] 8
DT[ J( "blah")]$y <- 3
Warning messages:
1: In[<-.data.table
(*tmp*
, J("blah"), value = list(a = "blah", :
NAs introduced by coercion
2: In[<-.data.table
(*tmp*
, J("blah"), value = list(a = "blah", :
Coerced 'double' RHS to 'character' to match the column's type; may have truncated precision. Either change the target column to 'double' first (by creating a new 'double' vector length 1 (nrows of entire table) and assign that; i.e. 'replace' column), or coerce RHS to 'character' (e.g. 1L, NA_[real|integer]_, as.*, etc) to make your intent clear and for speed. Or, set the column type correctly up front when you create the table and stick to it, please.
DT
x a y
1: NA 5 31�]0;david@LC2430HD:
�david@LC2430HD:$ exit
Script done on Wed May 14 01:02:33 2014
Submitted by: Michele Carriero; Assigned to: Arun ; R-Forge link
Hello, please consider the following two assignments to an element of a list column, which I think should not give the same result:
library(data.table)
dt <- data.table(id=1:2, comment=vector(mode="list", length=2))
dt[1L, comment := 1]
a<-dt$comment
dt[1L, comment := list(list(1))]
b<-dt$comment
> identical(a, b)
# [1] TRUE
This possible bug came up after a Arun's answer on SO:
Submitted by: shubh bansal; Assigned to: Arun ; R-Forge link
data.frame()
data frame with 0 columns and 0 rows
data.table(data.frame())
Empty data.table (0 rows) of 1 col: V1
Ideally the data.table
should have 0 columns
Organise current src/
by putting together a data.table.h
header file.
Submitted by: Arun ; Assigned to: Arun ; R-Forge link
duplicated.data.table documentation states that when the by argument is FALSE or NULL, it'll consider all the columns. However, by=FALSE will end up in error.
Even more, by=TRUE works the way by=FALSE should.
In an effort to fix this discrepancy, I'll remove the TRUE/FALSE dependency of 'by=' altogether and stick to by=NULL. No reason to have one logical argument working and the other ending in an error. Just more confusing.
Fix on the way.
Submitted by: Steve Lianoglou; Assigned to: Arun ; R-Forge link
Using v1.8.11 (rev 1170):
The drop=TRUE
parameter isn't being honored as it should. Witness that rows for "e" and "f" are included from dcast.data.frame, but not dcast.data.table:
library(reshape2)
library(data.table)
df <- data.frame(a=factor(sample(letters[1:3], 10, replace=TRUE), letters[1:5]),
b=factor(sample(tail(letters, 5), 10, replace=TRUE)))
dcast(df, a ~ b, drop=FALSE)
dt <- as.data.table(df)
dcast.data.table(dt, a ~ b, drop=FALSE)
Submitted by: Garrett See; Assigned to: Arun ; R-Forge link
The following did not give an error in 1.9.2, but does in 1.9.3. Using svn revision 1263:
library(data.table)
# data.table 1.9.3 For help type: help("data.table")
a <- data.table(BOD, key="Time")
b <- data.table(BOD, key="Time")[Time < 0] # zero row data.table
merge(a,b, all=TRUE) # works fine
# Time demand.x demand.y
#1: 1 8.3 NA
#2: 2 10.3 NA
#3: 3 19.0 NA
#4: 4 16.0 NA
#5: 5 15.6 NA
#6: 7 19.8 NA
merge(b,a, all=TRUE) # error
# Error in setcolorder(dt, c(setdiff(names(dt), end), end)) :
# neworder is length 2 but x has 3 columns.
Originally reported on the mailing list
Submitted by: Arun ; Assigned to: Arun ; R-Forge link
Best with an example:
require(data.table) ## 1.9.3
DT <- data.table(x=1:5, x=6:10)
DT[, 1:2, with=FALSE]
It's clear that the columns to choose are 1st and 2nd. Still, it gives back just the first column:
x x
1: 1 1
2: 2 2
3: 3 3
4: 4 4
5: 5 5
data.frame does this very nicely, although it renames the columns (which we don't have to do).
as.data.frame(DT)[, 1:2]
x x.1
1 1 6
2 2 7
3 3 8
4 4 9
5 5 10
Submitted by: Eduard Antonyan; Assigned to: Nobody; R-Forge link
This bug has been introduced some time between 1.8.11 and 1.9.2:
dt = data.table(a = 1:3, c = c("X", "P", "X"), d = 1:3, key = 'a')
dt[TRUE, sum(d), keyby = c]
# c V1
#1: X 4
#2: P 2
When not filtering, it works correctly, but the filtering screws something up:
dt[, sum(d), keyby = c]
# c V1
#1: P 2
#2: X 4
A couple more demos of the problem:
key(dt[TRUE, sum(d), keyby = c])
# [1] "c"
setkey(dt[TRUE, sum(d), keyby = c], c)
# Warning message:
# In setkeyv(x, cols, verbose = verbose) :
# Already keyed by this key but had invalid row order, key rebuilt. If you didn't go #under the hood please let datatable-help know so the root cause can be fixed.
Submitted by: Malcolm Hawkes; Assigned to: Nobody; R-Forge link
vec1 <- c("Corp", "CORP")
vec2 <- 1:3
dt <- CJ(vec1, vec2)
setkey(dt, V1, V2)
Creates warning
Warning in setkeyv(x, cols, verbose = verbose) :
Already keyed by this key but had invalid row order, key rebuilt. If you didn't go under the hood please let datatable-help know so the root cause can be fixed.
CJ creates
V1 V2
1: Corp 1
2: Corp 2
3: Corp 3
4: CORP 1
5: CORP 2
6: CORP 3
while doing setkey
And it’s keyed as you would expect by V1 then V2
key(dt)
[1] "V1" "V2"
But after doing setkey you have
V1 V2
1: CORP 1
2: CORP 2
3: CORP 3
4: Corp 1
5: Corp 2
6: Corp 3
Submitted by: K Davis; Assigned to: Arun ; R-Forge link
I create a test package with the following setup
NAMESPACE:
import(data.table)
export("testFunction")
DESCRIPTION:
Package: testPackage
Type: Package
Title: What the package does (short line)
Version: 1.0
Date: 2014-03-31
Author: Who wrote it
Maintainer: Who to complain to <[email protected]>
Description: More about what it does (maybe more than one line)
License: GPL (>= 2)
Imports: data.table (>= 1.9.3)
R/testFunction.R:
testFunction <- function() {
dt <- data.table(customerId=c(1:10),categoryId=c(1:10),unitSales=c(1:10))
invisible(dcast.data.table(dt,customerId~categoryId,value.var="unitSales",fill=0L))
}
For the full package see the attached tar.gz. I build the package, install it, and then use it as follows:
# R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
# Platform: x86_64-pc-linux-gnu (64-bit)
library(testPackage)
testFunction()
# Error in do.call("CJ", list(1:10, 1:10)) : could not find function "CJ"
This is the bug. The function testFunction()
can not find the data.table
function CJ()
despite the fact that data.table
was imported.
However, if I have the package depend upon data.table
, the problem goes away.
Looking at the sources for data.table 1.9.3 I see only one call of the form do.call(CJ...)
it is in the file data.table.R
in the function as.data.table.table()
which provides some of the as()
functionality for data.table
and is registered with R through the setAs()
From this behaviour my guess is that functions registered through setAs()
only have access to the globally available packages (The problem goes away when the import is replaced with a depends.). So, any functions registered through setAs()
should not depend upon functions exported from data.table as these functions need not be available in the environment setAs()
executed in.
So, my guess as to a solution would be to either re-implement the functionality of CJ()
in the function as.data.table.table()
or to find some other way of implementing as.data.table.table()
that does not require a call to CJ()
.
Submitted by: shubh bansal; Assigned to: Arun ; R-Forge link
In an empty data.table, defining a new column by reference by group does not add the column to the table.
In the example below, I would expect an empty column 'c' to be added to the data.table
dt1=data.table(a=character(0),b=numeric(0))
dt1
# Empty data.table (0 rows) of 2 cols: a,b
dt1[, c:=max(b), by='a']
dt1
# Empty data.table (0 rows) of 2 cols: a,b
Submitted by: Stephane Vernede; Assigned to: Arun ; R-Forge link
From version 1.9.2 (incluting latest 1.9.3 release) .BY is empty for all cases I have tested.
Consider
A<-data.table(fruit=c("apple","peach","pear"))
test<-function(x){
paste(x," ")
}
A[,test(.BY$fruit),by=c("fruit")]
returns
fruit V1
1: apple
2: peach
3: pear
Whereas
A[,test(fruit),by=c("fruit")]
returns the right answer
fruit V1
1: apple apple
2: peach peach
3: pear pear
My platform is R 3.0.2 on Win 7
Submitted by: Eduard Antonyan; Assigned to: Nobody; R-Forge link
Here's an example:
rm(dt)
rm(dt1)
dt = data.table()
dt[, {dt1 = data.table(a = 1:4); eval(parse(text = 'dt1[, a := 2]'))}]
It works fine without the eval/parse:
dt[, {dt1 = data.table(a = 1:4); dt1[, a := 2]}]
old and bad example, left here for reference
dt = data.table()
dt[, {eval(parse(text = 'print("boo")')); NULL}]
Pretty sure this is a recently introduced bug and it used to work before.
Submitted by: Mike Crowe; Assigned to: Arun ; R-Forge link
A minimal example the shows it is given below:
X = data.table(d = c(as.Date("2008-01-01"),as.Date("2008-01-01")), x = c(1,2))
X[, .SD[, d], by = d]
Result
d V1
1: 2008-01-01 13879
The .SD object has a column of numeric for d instead of date. Why does this matter? It matters when you are using the date in the j field calculation, for example:
X[, day(d) * sum(x), by = d]
returns an error which doesn't make a lot of sense at first (until you understand the above):
Error in as.POSIXlt.numeric(x, tz = tz(x)) : 'origin' must be supplied
This seems to be a new bug introduced recently.
Submitted by: Arun ; Assigned to: Arun ; R-Forge link
As shown here:
http://stackoverflow.com/q/23216033/559784
Submitted by: Nico S; Assigned to: Nobody; R-Forge link
It seems as grouping integer64 does not work for some numbers. Try:
dt1 <- data.table(id=as.integer64(c(86200,86201, 4797277036,9218868437227407266,47975577036, 86200,9218868437227307266, 4797277036,9218868437227407266,47975577036)), info=rep("a",10))
dt2 <- data.table(id=as.integer64(c(86200,4797277034, 4797277036,9218868437227407266)), info=c("d","e","f","g") )
dt3 <- merge(dt1,dt2,by="id")
dt3[,length(info.x),by=id]
It should be 2 for ID 86200. Found it by accident because it completely screwed the results in very big dataset.
But anyway, really great package. Appreciate it.
Submitted by: Jonathan Owen; Assigned to: Nobody; R-Forge link
I believe this didn't generate an error with earlier revisions. I'm using 1.8.11, r1158.
dt=data.table(id = 1:10, val1=10:1, val2=10:1)
dt[, sum(.SD), .SDcols="val1", by=id]
Error in gsum(.SD) : grpn [10] != length(x) [0] in gsum
5 gsum(.SD)
4 eval(expr, envir, enclos)
3 eval(jsub, thisEnv)
2[.data.table
(dt, , sum(.SD), .SDcols = "val1", by = id)
1 dt[, sum(.SD), .SDcols = "val1", by = id]
dt[, sum(.SD[, "val1", with=FALSE]), by=id]
id V1
1: 1 10
2: 2 9
3: 3 8
4: 4 7
5: 5 6
6: 6 5
7: 7 4
8: 8 3
9: 9 2
10: 10 1
Submitted by: Ricardo Saporta; Assigned to: Nobody; R-Forge link
If joining on a character column where the inner DT has no rows, a segfault occurs.
Reproducible example below
setkey(DT, A)
DT[ DT[FALSE] ]
DT[, A:= as.character(A)]
setkey(DT, A)
DT[ DT[FALSE] ]
sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] data.table_1.8.11 sos_1.3-8 brew_1.0-6
loaded via a namespace (and not attached):
[1] plyr_1.8 reshape2_1.2.2 stringr_0.6.2
ByteCompile: TRUE
Repository: R-Forge
Repository/R-Forge/Project: datatable
Repository/R-Forge/Revision: 1160
Submitted by: Stefan Fritsch; Assigned to: Nobody; R-Forge link
I'm sorry for the vague summary but I'm not really sure what the problem is.
First off unlike my previous issues I'm currently working with ASCII text, no Encoding issues.
Basically Version 1 (group then merge) fails some joins but not others. There is no obvious difference between the failed and joined values of Region like special characters or whatever.
Version 2 (merge then group), still a 100% data.table solution, works!
So the problem must happen during the grouping operation in A. I have no idea how or why.
Could we please get a slow version of merge as an option that uses a more robust character matching? Perhaps the built-in one? I like the speed but merge on character vectors is so fragile that you have to check every result separately which kinda defeats the purpose. =)
I'm sorry, I'll try to find a minimal working example over the next day, but I don't have the time for that right now.
D<-A[Year==2011,list(Spending=sum(y Spending
)),Region]
merge(D,
B[Year==2011],
by="Region")
merge(A[Year==2011],
B[Year==2011],
by="Region")[,list(Spending=sum(y Spending
)),Region]
merge(data.frame(A[Year==2011,list(Spending=sum(y Spending
)), Region]),
data.frame(B[Year==2011]),
by="Region")
Submitted by: Matthew Beckers; Assigned to: Arun ; R-Forge link
I came across this issue using version 1.8.10, and it is also discussed here by others http://lists.r-forge.r-project.org/pipermail/datatable-help/2013-June/001882.html
Submitted by: Arun ; Assigned to: Arun ; R-Forge link
This SO question explains nicely.
http://stackoverflow.com/questions/22375404/unable-to-use-evalparse-in-data-table-function
We've currently gone to 2E9 rows (the 32bit index limit) with 9 columns (100GB). See benchmarks page on wiki.
Ideally it would be great to compare all available tools that are either specifically developed for large in-memory data manipulation or are capable of handling data at these sizes much better than base. Of course base-R should also be included, typically as control.
Aspect of benchmarking should be to highlight not just run time (speed), but also memory usage. The sorting/ordering by reference, sub-assignment by reference etc.. features, for example, at this data size should display quite clearly on speed and memory gains attainable.
Submitted by: Benjamin Barnes; Assigned to: Arun ; R-Forge link
The names of the resulting data.table are in the incorrect order. For example,
set.seed(123)
DT <- data.table(XX = sample(LETTERS[1:5], 1000, replace = TRUE),
yy = sample(1:5, 1000, replace = TRUE))
as.data.table(DT[, table(XX, yy)])
## Names are c("yy", "XX", "N")
## Should be c("XX", "yy", "N"), as in as.data.frame
sessionInfo()
# R version 3.0.2 (2013-09-25)
# Platform: x86_64-w64-mingw32/x64 (64-bit)
# locale:
# [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252
# [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C
# [5] LC_TIME=German_Germany.1252
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
# other attached packages:
# [1] data.table_1.9.2
# loaded via a namespace (and not attached):
# [1] plyr_1.8.1 Rcpp_0.11.0 reshape2_1.2.2 stringr_0.6.2 tools_3.0.2
Submitted by: William Constantine; Assigned to: Nobody; R-Forge link
Want to crash your R session? Then read on …
In R, negative indexing is often used to get rid of the corresponding elements/rows in a vector/data frame. With data table objects, however, you have to be careful:
library(data.table)
data.table 1.8.10 For help type: help("data.table")
DT <- data.table(x = 1:5, y = 5:1)
DT
x y
1: 1 5
2: 2 4
3: 3 3
4: 4 2
5: 5 1
ix <- c(1L, 3L, 5L)
DT[ix]
x y
1: 1 5
2: 3 3
3: 5 1
DT[-ix]
x y
1: 2 4
2: 4 2
DT[-ix, z := 5L]
DT # prepare for meltdown now …
DT # … or now
DT[!ix, z:= 5L]
DT
x y z
1: 1 5 NA
2: 2 4 5
3: 3 3 NA
4: 4 2 5
5: 5 1 NA
While I understand the use of ! is documented and preferred, it shouldn't bring down R if someone mistakenly uses minus (-) instead! Here are additional specs:
Thanks!
William Constantine
[email protected]
Package: data.table
Version: 1.8.10
Maintainer: Matthew Dowle [email protected]
Built: R 3.0.2; x86_64-w64-mingw32; 2013-10-07 15:31:26 UTC; windows
R Version:
platform = x86_64-w64-mingw32
arch = x86_64
os = mingw32
system = x86_64, mingw32
status =
major = 3
minor = 0.2
year = 2013
month = 09
day = 25
svn rev = 63987
language = R
version.string = R version 3.0.2 (2013-09-25)
nickname = Frisbee Sailing
Windows 7 x64 (build 7601) Service Pack 1
Locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
Search Path:
.GlobalEnv, package:data.table, package:stats, package:graphics,
package:grDevices, package:utils, package:datasets, package:methods,
Autoloads, package:base
This package has a bug submission web page, which we will now attempt
to open. The information above may be useful in your report. If the web
page doesn't work, you should send email to the maintainer,
Matthew Dowle [email protected].
Submitted by: Arun ; Assigned to: Arun ; R-Forge link
This is a regression due to recent changes to [.data.table
, I think. Basically,
data.table(1:10)[, -1L, with=FALSE]
should return null data.table, but instead errors with lhs
not found - it's in the wrong place (much further than where it should've already stopped).
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