similar to: comparing reshape's

At first sorry for the possibly dumb question of a newbie. I am using the hydrogeo package to visualize approx. 300 data within the Piper-Hill diagrams. The package is using a dataframe with 6 columns, first of them is containing the row.names, next four with the data itself. The last column contains "WaterTypes" dividing data to several categories. The diagram is created by the

dear R wizards:? I am wrestling with reshape.? I have a long data set that I want to convert into a wide data set, in which rows are firms and columns are years. > summary(rin) firm fyear sim1 Min. :1004.00 Min. :1964.0 Min. : -1.00000 1st Qu.:1010.00 1st Qu.:1979.0 1st Qu.: -0.14334 Median :1016.00 Median :1986.0 Median : 0.00116 Mean

When finally got some time to do some coding, I started and stopped right after. The stationary test is a good starting point because it demonstrates how we should be able to move the very basic R matrices. I have a real- world small N data set with rows: id(n=1)---t1---variable1 ... id=(N=20)---T=21---variable1 Thus, a good test case. For first id I was considering something like this: lag

I am a relative R newbie and I am having trouble with reshape() on R V1.9.1 on Linux. The same code appears to be ok when run on R V2.2.0 on Windows and a V2.1 on Linux. Any help would be great as I need to stay on V1.9 for the immediate future... Thanks, Reid Hutchins df <- data.frame(state= rep(1:2, each=8), school=rep(1:2,each=4), class=rep(1:2,each=2),Values2Columns=rep(1:2,

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

Hi all: I solved the previous stated problem in something of a brute force way (but it works). I seem to now be running into one little hiccup using reshape. Here is a quick snip of the data in long format: grade stability year schid 6 Grade 4 3 2001 100005 7 Grade 4 3 2002 100005 8 Grade 4 2 2003 100005 10 Grade 5 2 2001 100005 11 Grade 5

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

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 <-

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,

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hello R-Help: I would really appreciate some help on this. I have spent a good deal of time searching for an answer for what I would think to be a common practice: Subclasses an S4 class from a data.frame. But have found very little. Here is some sample code that I've been trying: setClass("MyDataFrame",

I would appreciate some advice on the following task. I have some data that currently looks like this: t1 <- data.frame(id=c(1,1,2,2), aspect=c("A","B","A","B"), score=c(10,9,11,12)) I'd like it to look like this: id A B 1 10 9 2 11 12 reshape() looks like a good candidate for this job but I'm not really sure about the roles of

I have two data frames with a number of common variables that I wish to put into "long format". The first contains the variables es(Csales) [1] "terr" "Dec.02" "Jan.03" "Feb.03" "Mar.03" "Apr.03" "May.03" "Jun.03" [9] "Jul.03" "Aug.03" "Sep.03" "Oct.03"

Hello I am reshaping a data.frame bids --> reshaped as shown below. I thought this should be possible with a single invocation of reshape, but the only way I came up with is reshaping subsets for each keyword and then joining them together. Does anyone have an idea how to solve this in a more elegant way? Efficiency is a concern as the datasets are very large. Is there a way to specify

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 =

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

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

Hello everybody, I have been recently using reshape to convert "long" data to "wide" data. Everything was going well until I reached some problematic datasets. It has taken me a couple of weeks to finally figure out what might be happening. The problem is reproducible with test cases, and on two versions of R (Windows 2.2.0 and x86-64 Fedora Core 3 R 2.2.0). The data

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

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

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