Displaying 20 results from an estimated 2000 matches similar to: "How to Derive an S4 Class from a data.frame?"
2011 Sep 08
2
Variable scoping question
I modified an example in the object.size help page to create a function
I want to be able to run:
"mysize" <- function() {
z <- sapply(ls(), function(w) object.size(get(w)))
as.matrix(rev(sort(z))[1:5])
}
mysize()
When I test the lines inside the function it works fine:
> z <- sapply(ls(), function(w) object.size(get(w)))
> as.matrix(rev(sort(z))[1:5])
2010 Apr 13
1
Using object.size inside a function
When I encounter memory errors, I like to see the size of the objects in
memory, so I modified one of the examples:
z <- sapply(ls(), function(x) object.size(get(x)))
as.matrix(rev(sort(z))[1:10])
This works fine if I run it as is, but if I try to place it inside a
function, I get an error (see below). I tried using sort.list and
unlist, but I couldn't get it to work. I
2007 Sep 08
1
ggplot legend consolidation
Hello Everyone,
I have recently been introduced to the ggplot package by Hadley Wickham
and must say I am quite impressed so far at how easy it is to make
attractive plots, but one thing I am struggling over is how to
consolidate legends.
I have 3 plots that I would like to put on a single page and all 3 map
the same dimension of the data to the colour aesthetic. Right now, when
I plot all
2011 May 27
1
Reference Classes/S4 Classes: can method dispatch check superclasses BEFORE resorting to method for "ANY"?
Dear list,
is it possible that method dispatch checks for superclasses/virtual
classes before checking "ANY"?
I'd like to build a generic initialization method for all my Reference
Class (say "MyDataFrame") objects by having them inherit from class, say
"MyRefClassVirtual" (which would have to be a virtual S4 class; there
are no virtual Reference Classes,
2009 Dec 08
1
problem with split eating giga-bytes of memory
I'm having trouble using split on a very large data-set with ~1400 levels of
the factor to be split. Unfortunately, I can't reproduce it with the simple
self-contained example below. As you can see, splitting the artificial
dataframe of size ~13MB results in a split dataframe of ~ 144MB, with an
increase memory allocation of ~10 fold for the split object. If split scales
linearly, then my
2011 May 26
0
Reference Classes: getter and setter functions/methods and possible shortcuts
Hi everyone,
just wanted to ask what's the smartest/recommended way of defining
getter and setter function *shortcuts* (i.e. something like "[", "[<-")
for Reference Class objects?
Or is it desired to not use this stuff, but define methods like
'obj$getSubset(row=1:3, col=1)' and 'obj$setSubset(value=x)' instead?
I have some example code that might
2010 Mar 11
2
Can't convert list to matrix properly
Hi guys, here is a list of names that I have:
MyList:
> myList<-list("A", "B","C","D")
> myList
[[1]]
[1] "A"
[[2]]
[1] "B"
[[3]]
[1] "C"
[[4]]
[1] "D"
I want to turn this list into a matrix of 1 row and 4 columns with those
four components (A, B, C, D) so here is what I do:
myDataFrame <-
2011 Apr 07
3
Correlation Matrix
Listers,
I have a question regarding correlation matrices. It is fairly straight
forward to build a correlation matrix of an entire data frame. I simply use
the command cor(MyDataFrame). However, what I would like to do is construct
a smaller correlation matrix using just three of the variable out of my data
set.
When I run this:
cor(MyDataFrame$variable1,
2007 Oct 24
3
Partial aggregate on sorted data
Hi All,
I'm looking for ways to compute aggregate statistics (with the aggregate
function) but with an option for sorting and selecting a subset of the data
frame. For example, I have would like to turn this :
aggregate(myDataframe$TargetValue,list(SomeFactor =
myDataframe$SomeFactor),mean)
into something like
aggregate(myDataframe$TargetValue,list(SomeFactor =
2007 Apr 22
1
dput/dget when a data frame has 2 rows (PR#9627)
This doesn't seem right; I'm using R version 2.4.1 (2006-12-18) on Mac OS
and Win XP and find the same issue:
> mydataframe <- data.frame(ppi=c(.5,.5),mmu=c(5,10))
> dput(mydataframe,"mydataframe.txt")
> dget("mydataframe.txt")
Error in attributes(.Data) <- c(attributes(.Data), attrib) :
row names must be 'character' or 'integer', not
2010 May 15
1
Dataframe to word, using R2wd
Hi All,
I'm trying to use R2wd to send a dataframe to Word. The dataframe
isn't huge - 300 rows, 12 variables, although it has some long strings
in it.
Using:
wdTable(format(myDataFrame))
or
wdTable(myDataFrame)
Produces a very complex table, which Word struggles to process and
layout. (I can't work out what the table is - it seems to be nested
tables. Converting to text gives
2012 Jul 04
2
Difference between two-way ANOVA and (two-way) ANCOVA
Hi!
as my subject says I am struggling with the different of a two-way ANOVA and
a (two-way) ANCOVA.
I found the following examples from this webpage:
http://www.statmethods.net/stats/anova.html
# One Way Anova (Completely Randomized Design)
fit <- aov(y ~ A, data=mydataframe)
# Randomized Block Design (B is the blocking factor)
fit <- aov(y ~ A + B, data=mydataframe)
# Two Way
2005 Jun 15
1
anova.lme error
Hi,
I am working with R version 2.1.0, and I seem to have run into what looks
like a bug. I get the same error message when I run R on Windows as well as
when I run it on Linux.
When I call anova to do a LR test from inside a function, I get an error.
The same call works outside of a function. It appears to not find the right
environment when called from inside a function. I have provided
2006 Oct 05
1
Aggregate Values for All Levels of a Factor
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1
Hello,
I'm a novice user trying to figure out how to retain NA aggregate
values. For example, given a data frame with data for 3 of the 4
possible factor colors("orange" is omitted from the data frame), I want
to calculate the average height by color, but I'd like to retain the
knowledge that "orange" is a possible factor,
2005 Apr 04
2
mysql retrive question
hello R-Users,
I have this simple but not for me question:
I do:
> res<-dbSendQuery(con, "SELECT * FROM tabellaProva")
> myDataFrame<-fetch(res)
> myDataMatrix<-as.matrix(myDataFrame[,-1])
> namerows(myDataMatrix)<-as.character(myDataFrame[,1])
and I have:
io tu
io "0" "1"
tu "1" "0"
my problem is that the
2010 Apr 26
1
Sweave: centering with echo=TRUE
In a .Rnw file I want to insert the R command
pairs(mydataframe)
and achieve the following effects
1. the command itseld is echoed into the tex document generated by Sweave
<<fig=TRUE,echo=TRUE>>=
2. The graphics generated appears in the tex document, with the graphics
centred.
3. The R command > pairs(mydataframe) is not centered.
Sweave-manual.pdf gives the following code chunk
2010 Apr 29
2
understanding behavior of "merge"
I'm trying to bootstrap resample from a repeated measures dataset. I sample
a vector of "ID"'s from my dataframe with replacement.
Then I merge this back with my dataframe.
I'm re-sampling subjects in the dataset rather than rows of the data.
I thought I could use the left/right join features of the merge to select
the records I want from the dataframe (mydataframe), like
2012 Jul 19
2
problem with using apply for dataframe
Dear people,
I am including an example of a dataframe:
mydataframe<-data.frame(X=c(1:4),total_bill=c(16.99,10.34,21.01,23.68),tip=c(1.01,1.66,3.50,3.31),sex=c("Male","Male","Male","Female"))
When I use the sapply function getting the information about the factors
works:
sapply(mydataframe,function(x)is.factor(x))
X total_bill tip
2008 Oct 29
0
Propagate vector attributes to data frame
Hello,
I've got a function that takes a numeric vector (x), computes a
transformation value (myAttr) for x, transforms x according to myAttr
and then sets myAttr as an attribute of x before returning x, so I can
easily know what myAttr was used (basically it's a power transformation
and myAttr is the lambda).
myFunction.numeric <- function(x, ...) {
myAttr <- calcMyAttr(x, ...)
x
2011 Dec 22
1
ff object in lapply function
Hello. I'm using as.ffdf(mydataframe) to create ffdf objects inside an lapply
loop and returning that. I then use crbind to combine the lapply results
into allData.
So...simplified flow looks like this.
res <- lapply(1:nchunks, function(n)
{
blah blah with nth chunk
mydataframe <- data.frame(blah blah)
dat <-