similar to: transforming table into data frame

How can I draw a 3D perspective of a contingency table, that is showing 3D bars whose height is in proportion of the table cells? --------------- Charles RAUX, Laboratoire d'Economie des Transports CNRS-Universit? Lumi?re Lyon 2-ENTPE email : charles.raux at let.ish-lyon.cnrs.fr http://www.ish-lyon.cnrs.fr/let -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Before I reinvent the wheel, I have need for a relatively straightforward crosstabulation (2 x n) function. I know that R has table(), ftable(), xtabs(), and summary(xtabs()), but none of these produce a fully "tricked" out cross-tabulation with marginal totals, expected cell frequencies, and an array of statistics about the contingency table. Is there a more complete (something

I have an application that would generate a cross-tabulation in array format in R. In particular, my application would give me a result similar to that of : array(5,c(2,2,2,2,2)) The above could be seen as a cross-tabulation of 5 variables with 2 levels each (could be 0 and 1). In this case, the data were such that each cell has exactly 5 observations. I Now, I want the output to look like the

Hi all, Please, is there any way of controlling factors in row/columns when using ftable/xtabs? As far as I can see, the last cross-clasifing variable in the formula will appear in columns. The previous ones, in rows. For instance, is it possible to make tension and replicate appear in columns? ftable(xtabs(breaks ~ wool + tension + replicate, data = warpbreaks)) After some years using SAS

Hi, I am trying to reproduce some functionalities of Excel pivot table in R, sadly, I couldn't figure out how to do it. I am wondering if this is even possible in R. Does anyone know? Here is an example: year=rep(2003,16) quarter=rep(1:4,each=4) sales=1:16 company=rep(c("a","b","c","d"),4) df=data.frame(year,quarter,sales,company) #this is the

I am trying to restart on R after 2 months stop. Start with previously functioning procedure: "ch<-odbcConnect("dBase Files")" get "Warning message: ODBC connection failed in: odbcConnect("dBase Files") " I have tried unsuccessfully different working directories. The only change I see is that I am working with a new login account on the same machine.

Hi I haven't found a way to produce a tabulation from factor data with NA values using xtabs. Please find a minimal example below, it's also on R-pubs [1]. Tested with R 3.1.2 and R-devel r67720. It doesn't seem to be documented explicitly that it's not supported. From reading the code [2] it looks like the relevant call to table() doesn't set the "useNA"

I have a sparse contingency table (most cells are 0): > xtabs(~.,data[,idx:(idx+4)]) , , x3 = 1, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 31 2 0 0 112 3 0 0 94 , , x3 = 2, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 3, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 1, x4

Hi, I'm using R version 1.8.0 on Windows NT. When fitting a glm with Poisson random component and a log link, I frequently need to include an offset. Typically I use xtabs or table to get the counts for the contingency table, and then I use as.data.frame.table to create a data frame that I can use in the glm function. I have not found an option that allows me to total the offset variable to

A disturbing behaviour of R: an import of data using RODBC library (Windows 98, R 1.1.1) recognizes accented characters in variables names but these can't be manipulated further. See below: > library(Rodbc) > ch<-odbcConnect("Paradox Files") > pollut<-sqlFetch(ch,Pollutio) > pollut Mortalit? Densit? Pollution 1 82 600 110 2 97 960

Dear List, I would appreciate help on the following matter: I am aware that higher dimensional contingency tables can be analysed using either log-linear models or as a poisson regression using a generalized linear model: log-linear: loglm(~Age+Site, data=xtabs(~Age+Site, data=SSites.Rev, drop.unused.levels=T)) GLM: glm.table <- as.data.frame(xtabs(~Age+Site, data=SSites.Rev,

Some naive questions: 1) How to remove a column in a data frame? I expected that rm would work but this is not the case (e.g. rm(dat$yyy) gives Warning message: remove: variable dat$yyy was not found). I only found to assign NULL value (e.g.: dat$yyy<-NULL). Is it the right way? 2) Is the place formerly occupied by dat$yyy automatically gained by R for other uses? 3) If t1 and t2 are 2 only

I want to get subsets averaged on numeric variables number 5:13 but I get the error below that I cannot understand. > is.factor(dat$Statut) [1] TRUE > s<-ave(dat[,5:13],dat$Statut) Error in [<-.data.frame(*tmp*, , value = if (n) { : Argument "i" is missing, with no default Thanks in advance --------------- Charles RAUX, Laboratoire d'Economie des Transports

I use hierclust (hierarchical clustering) in multiv package. In the documentation it is said that plclust (plotting a dendrogram) is available in S-plus. Can I find it anywhere (I have searched through http://lib.stat.cmu.edu/S and found only quotations of plclust in multiv) or is it only part of the S package (which I don't have)? Thanks --------------- Charles RAUX, Laboratoire

Dear list, I am trying to make a contingency table with xtabs but I am getting a 0 where I expect a 'NA'. Here is a simple example: options(stringsAsFactors = FALSE) rn <- LETTERS[1:4] df1 <- data.frame(r07 = rep(rn, each=4), r08 = rep(rn, 4), value = 1:16) xtabs(value ~ r07 + r08, df1) # Delete the combination [A, C] df1 <- df1[-3,] # Set 'value'

3 general questions: 1) How can I have the plot History Recording automatically turned on each time I start R (Windows)? 2) How can I have some libraries automatically loaded at R start? 3) As far as I know weights can be specified only for lm. How can I take account of weights with a weighted sample in other models or functions (table but also other multivariate and cluster techniques)? Thanks

Hi, I've been trying to sort the values of the factors of contingency tables generated with xtabs. For example, I have a factor called "artic" with three possible values that I would like to order in a specific way -- but I'm not sure how to go about this. > test <- read.table("test.tab",header=TRUE,sep="\t") > artic =

Hi, I am constructing a contingency table using xtabs. The function works great: mo yr Sep Oct Nov Dec 1950 -7.164486e-02 3.152674e-02 -1.283389e-02 1.570382e-01 1951 3.054293e-02 4.665234e-02 -2.445499e-04 8.720204e-02 1952 3.937034e-02 -4.790636e-02 5.022616e-02 1.180279e-01 but I wonder if there is an argument I can pass to xtabs

Hello. Does anyone know of an existing function that takes a list in the form of: Plot1 Species1 Abundance1 Plot1 Species2 Abundance2 Plot2 Species1 Abundance1 Plot2 Species3 Abundance3 . . . PlotN SpeciesN AbundanceN and translates into a matrix in the form of Species1 Species2.... SpeciesN Plot1 Abundance1 Abundance2... AbundanceN Plot2 Abundance1

After searching in R- Introduction, FAQ, help... I don't understand this: I write a function in a file (.R): tt <- function(mc) { date() mc<-read.csv2("machines.txt",na.strings="") date() } I source it in R and I type tt(). The answer is > tt() [1] "Mon Aug 14 11:18:25 2000" > The instructions following the first "date()" are ignored. Why?