similar to: adding labels to tapply results

Hello, I'm trying to use tapply to find group means in a function. It works outside of a function, but I get the error message from the following code: "Error in tapply(index, cluster, mean) : arguments must have same length." Any suggestions? Thanks. eric d <- data.frame(cbind(cluster=1:2, value1=1:10, value2=11:20)) d FindClusterTraits <- function(framename, index){

Hi, I have a vector of data, that I group based on two factors via tapply. For each such grouping I would like to plot a pie chart. I can layout these pie charts in a matrix layout, correpsonding to the levels of the two factors. But I am getting stuck on how to label the rows and colums. My current approach looks like this: x <- data.frame(obs=sample(c('low', 'high'),100,

Hi, there I'm trying to plot what is returned from a call to tapply, and can't figure out how to do it. My guess is that it has something to do with the inclusion of row names when you ask for the values you're interested in, but if anyone has any ideas on how to get it to work, that would be stellar. Here's some example code: y1<-rnorm(40, 2) x1<-rep(1:2, each=20)

Hei, i am trying to plot the means of two variables (d13C and d15N), by 2 grouping factors (Species and Year) that i obtained by the function tapply. I would like to plot with different colours according to the Year and show the "Species" as data labels. My data looks like this: Species d13C d13N Year "Species1" 14,4 11.5 2009 "Species2"

Dear R users, I have a newbie-question that I couldn't resolve after reading through several pieces of documentation and searching the archive. I have a data.frame containing experimental data from a group experiment in psychology. Each line represents a single participant, but participants were assigned to groups of three or four persons. One variable indicates each participants'

Hi, I try to apply a function to subsets of a data.frame. tapply() does the job, but the as output, I am looking for a vector (not an array/matrix) ordered in the same way as the original data, so I can simply cbind the result to the original data.frame. Below is a minimal example. I know that there are packages that can do these things easier, but I'm looking for a fast solution not

Dear all, I wanted to make a two-way-table of two variables with a counting variable stored in another column of a dataframe. In version 1.9.1, the behavior is as expected as shown in the simplified example code. > sex <- rep(c("F", "M"), 5) > income <- c(rep("low", 5), rep("high", 5)) > count <- 1:10 > mydf <-

Dear list, I have the function (as a simple example, which is actually part of a larger function) pres.test<-function(N0=N0, N1=N1) { dt<-5 r<-log(N1/N0)/dt r } which calculates the annual growth rates in a population Where N0 is the population classified into age intervals, say 5 years, at time=1995, and N1 is the population by 5 year age classes at time=2000.

Dear List, why does this not work? df <- data.frame(var1 = c(3,2,1), var2 = c(6,5,4), var3 = c(9,8,7), fac = c('A', 'A', 'B')) tapply(cbind(df$var1, df$var2, df$var3), df$fac, mean) Thank you, Stefan

Hi, I'm building a matrix m from a data frame d which includes the matrix row, column and value. This works well enough: m <- tapply(d[,"value"],d[,c("row","column")],c) However, I'd like to replace any missing values with 0, not NA. The obvious doesn't work, however: m <-

I am working with a longitudinal data set in the long format. This data set has three observations per grade level per year. Here are the first 10 rows of the data frame: >tenn.dat[1:10,] year schid type grade gain se new cohort 6 2001 100005 5 4 33.1 3.5 4 3 7 2002 100005 5 4 33.9 3.9 4 2 8 2003 100005 5 4 32.3 4.2 4 1 10 2001 100005

I'm interested in a version of tapply() that operates with shingles instead of factors. For instance: x <- c(1,1,2,2,3,3) y <- c(1,1,1,0,0,0) s <- shingle(x,intervals=cbind(c(0.5,1.5),c(2.5,3.5))) # the following function should exist! tapply.shingle(x,s,mean) # returns the vector c(0.75,0.25) I've written such a function as follows: tapply.shingle <-

I read answers to questions including the words "tapply" and "weighted.mean", but I didn't understand either the problem (data) or the solution provided. Here is my question ... > dat[1:10,] GROUP VALUE FREQUENCY 1 2 2 78 2 2 3 40 3 2 4 16 4 2 5 3 5 2 6 1 6 2 8 1 7

After some fiddling around with the tapply command, I discovered that the factors (the INDEX argument) given to tapply must be specified in fastest-cycling first order. The following code shows how I discovered my error: (R version 1.2.1) -o-o-o-o-o- x <- as.data.frame(list(data=c(-9,0,3,1,-9,1,0,-9,0,3,1,-9,1,0), subj=c(rep(1,7),rep(2,7)),

I am getting a difference in results when running some analysis using by and tapply compare to using a for loop. I've tried searching the web but had no luck with the keywords I used. I've attached a simple example below to illustrates my problem. I get a difference in the mean of yvar, diff and the p-value using tapply & by compared to a for loop. I cannot see what I am doing wrong.

I have a data file that looks like this class pigeon falcon propeller jet wing fly birds 25 37 0 0 2 1 planes 0 1 28 40 1 3 birds 19 41 0 1 4 6 planes 0 0 25 50 5 5 planes 1 0

Hi R-users, I'm quite new to R and trying to learn the basics. I have a following problem concerning the convertion of array object into data frame. I have made following data sets tmp1 <- rnorm(100) tmp2 <- gl(10,2,length=100) tmp3 <- as.data.frame(cbind(tmp1,tmp2)) tmp3.sum <- tapply(tmp3$tmp1,tmp3$tmp2,sum) tmp3.sum <- as.data.frame(tapply(tmp1,tmp2,sum)) and I want the

I think I understand tapply but i still can't figure out how to do the following. I have a dataframe where some of the column names are the same and i want to make a new dataframe where columns that have the same name are averaged by row. so, if the data frame, DF, was AAA BBB CCC AAA DDD 1 0 7 11 13 2 0 8 12 14 3 0 6 0 15

Hello! I have data frame with 'weights' in one of the columns. I need to compute weighted mean on another column other factor variable and i am trying to: res<-tapply(data$k,list(data$model),weighted.mean,w=data$w,na.rm=T) and i get: Warning messages: 1: longer object length is not a multiple of shorter object length in: x * w 2: longer object length is not a multiple of shorter

Hey! Could you please take a quick look at what I have done? Somehow I get wrong results using the anova(lm()) combination compared to doing a two way ANOVA by hand. Running: Data<-read.table("Data.txt"); g<-lm(ExM~S1*S2,Data); anova(g); Gives: Analysis of Variance Table Response: ExM Df Sum Sq Mean Sq F value Pr(>F) S1 1 4.3679