Displaying 20 results from an estimated 600 matches similar to: "New package: plyr"
2012 Jan 12
1
parallel computation in plyr 1.7
Dear all,
I have a question regarding the possibility of parallel computation in plyr
version 1.7.
The help files of the following functions mention the argument '.parallel':
ddply, aaply, llply, daply, adply, dlply, alply, ldply, laply
However, the help files of the following functions do not mention this
argument: ?d_ply, ?aply, ?lply
Is it because parallel computation is not
2009 Apr 15
0
plyr version 0.1.7
plyr is a set of tools for a common set of problems: you need to break
down a big data structure into manageable pieces, operate on each
piece and then put all the pieces back together. For example, you
might want to:
* fit the same model to subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise transformations like scaling or standardising
*
2009 Apr 15
0
plyr version 0.1.7
plyr is a set of tools for a common set of problems: you need to break
down a big data structure into manageable pieces, operate on each
piece and then put all the pieces back together. For example, you
might want to:
* fit the same model to subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise transformations like scaling or standardising
*
2010 Sep 10
0
plyr: version 1.2
plyr is a set of tools for a common set of problems: you need to
__split__ up a big data structure into homogeneous pieces, __apply__ a
function to each piece and then __combine__ all the results back
together. For example, you might want to:
* fit the same model each patient subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise transformations
2010 Sep 10
0
plyr: version 1.2
plyr is a set of tools for a common set of problems: you need to
__split__ up a big data structure into homogeneous pieces, __apply__ a
function to each piece and then __combine__ all the results back
together. For example, you might want to:
* fit the same model each patient subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise transformations
2010 Oct 03
1
plyr: a*ply with functions that return matrices-- possible bug in aaply?
I have an application where I have a function to calculate results for
a 2-way table or matrix, which
returns a matrix with one less row and column. To keep this short, the
function below captures the structure:
fun2way <- function(f){
if (!length(dim(f)) ==2) stop("only for 2-way arrays")
R <- dim(f)[1]
C <- dim(f)[2]
f[1:(R-1), 1:(C-1)]
}
Now, I want to
2011 Apr 11
0
plyr: version 1.5
# plyr
plyr is a set of tools for a common set of problems: you need to
__split__ up a big data structure into homogeneous pieces, __apply__ a
function to each piece and then __combine__ all the results back
together. For example, you might want to:
* fit the same model each patient subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise
2011 Apr 11
0
plyr: version 1.5
# plyr
plyr is a set of tools for a common set of problems: you need to
__split__ up a big data structure into homogeneous pieces, __apply__ a
function to each piece and then __combine__ all the results back
together. For example, you might want to:
* fit the same model each patient subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise
2013 Feb 01
0
R code parallelized using plyr and doMC: error message: Error in do.ply(i) : task 1 failed - “could not find function ”getClass“”
Dear list,
I'm just getting started learning how to use remote supercomputers for
execution of parallelized code. I got a lot of initial help from this
<http://stackoverflow.com/questions/14553357/parallelizing-on-a-supercomputer-and-then-combining-the-parallel-results-r>
previous post, as well as one particularly helpful and patient XSEDE guy.
I'm only using one node (for the
2012 Jun 05
1
Trouble with Functions
Hi guys,
I'm a new to R and following along with Tutorials using this book:
http://www.amazon.com/Practical-Statistical-Analysis-Non-structured-Applications/dp/012386979X
In one of them, they use the twitteR package and describe the following
function (see below). From what I can tell from the documentation (R),
there's a method to call it directly in an interactive session. The way
2010 Apr 29
1
Using plyr::dply more (memory) efficiently?
Hi all,
In short:
I'm running ddply on an admittedly (somehow) large data.frame (not
that large). It runs fine until it finishes and gets to the
"collating" part where all subsets of my data.frame have been
summarized and they are being reassembled into the final summary
data.frame (sorry, don't know the correct plyr terminology). During
collation, my R workspace RAM usage goes
2009 Sep 25
2
summarize-plyr package
Hi,I am using the amazing package 'plyr". I have one problem. I would
appreciate help to fix the following error: Thanks.
______________________________
> library(plyr)
> data(baseball)
> summarise(baseball,
+ duration = max(year) - min(year),
+ nteams = length(unique(team)))
Error: could not find function "summarise"
> ddply(baseball, "id", summarise,
+
2010 Jul 27
0
plyr version 1.1
plyr is a set of tools for a common set of problems: you need to break
down a big data structure into manageable pieces, operate on each
piece and then put all the pieces back together. For example, you
might want to:
* fit the same model to subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise transformations like scaling or standardising
2010 Jul 27
0
plyr version 1.1
plyr is a set of tools for a common set of problems: you need to break
down a big data structure into manageable pieces, operate on each
piece and then put all the pieces back together. For example, you
might want to:
* fit the same model to subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise transformations like scaling or standardising
2011 Jan 04
0
plyr 1.4
# plyr
plyr is a set of tools for a common set of problems: you need to
__split__ up a big data structure into homogeneous pieces, __apply__ a
function to each piece and then __combine__ all the results back
together. For example, you might want to:
* fit the same model each patient subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise
2011 Jan 04
0
plyr 1.4
# plyr
plyr is a set of tools for a common set of problems: you need to
__split__ up a big data structure into homogeneous pieces, __apply__ a
function to each piece and then __combine__ all the results back
together. For example, you might want to:
* fit the same model each patient subsets of a data frame
* quickly calculate summary statistics for each group
* perform group-wise
2009 Sep 28
4
How to assess object names within a function in lapply or l_ply?
Dear All,
to produce output of several columns of a data frame, I tried to use
lapply and also l_ply. In both cases, I would like to print a header
line containing also the name of the respective column in the data frame.
For example, I would like the following
lapply(data.frame(a=1:3, b=2:4), function(x) print(deparse(substitute(x))))
to produce:
[1] "a"
[1] "b"
and
2009 Nov 19
4
Is there an variant of apply() that does not return anything?
There are a few version of apply() (e.g., lapply(), sapply()). I'm
wondering if there is one that does not return anything but just
silently apply a function to the list argument.
For example, the plot function is applied to each element in 'alist'.
It is redundant to return anything from apply.
apply(alist,function(x){ plot each element of alist})
2010 Jan 29
1
SemiPar/spm question
Hello -- I posted this question yesterday and for some reason the post seems to be attached to the wrong thread. Also, I extended my test a little and it seems to indicate the problem is with spm. I would appreciate any help. Thanks.
==========================================================
library(plyr)
library(SemiPar)
data <-
2012 Apr 10
1
plyr: set '.progress' argument to default to "text"
Dear all
Is it possible to set globally the option .progress = "text" to all
the apply functions in 'plyr'. For example, current default is
daply(..., .progress = "none"). I would like to set it to daply(...,
.progress = "text"), so as to avoid writing the argument every time I
call such a function. I looked into ?daply and ?create_progress_bar
without much