similar to: data.frame - how to calculate the number of rows

Hello, using the syntax aggregate(daten[,c(3,4)], list(A,B), mean) I'm getting the following data.frame: A B C D 1 35 1 6.16000 5 2 47 1 31.24333 20 3 54 1 26.81773 2 4 3 2 12.99000 7 5 4 2 6.49000 1 C and D are both means. But now I want to

Dear users, I'm trying to learn how to use the "...". I have written a function (simplified here) that uses doBy::summaryBy(): # 'dat' is a data.frame from which the aggregation is computed # 'vec_cat' is a integer vector defining which columns of the data.frame should be use on the right side of the formula # 'stat_fun' is the function that will be run to

Hello Everyone- I'm calculating summary statistics on a dataset (~4000 records, observations are not uniformly distributed) using summaryBy and trying to add a column with the number of observations to the output as well. What occurs to me is to use nrow(), but this doesn't appear to be working I'm able to replicate the same results with an example from the summaryBy docs:

Hi, I had the following code: testp <- rcorr(t(datcm1),type = "pearson") mat1 <- testp[[1]][,] > 0.6 mat2 <- testp[[3]][,] < 0.05 mat3 <- mat1 + mat2 The resulting mat3 (smaller version) matrix looks like: NA 0 0 0 0 NA 0 NA 0 0 NA 2 0 0 2 NA To get to the number of times a '2' appears in the rows, I was

Hi Folks, I'm trying to cut my data inside the summaryBy function. Perhaps formulas don't work that way? I'd like to avoid adding another column if possible, but if I have to, I have to. Any ideas? Thanks, Allie require(doBy) df = dataframe(a <- rnorm(100), b <-rnorm(100)) summaryBy(a ~ cut(b,c(-100,-1,1,100)), data=df) # preferred solution, but it throws an

Dear Soren and R users: I am trying to use the summaryBy function with weights. Is this possible? An example that illustrates what I am trying to do follows: library(doBy) ## make up some data response = rnorm(100) group = c(rep(1,20), rep(2,20), rep(3,20), rep(4,20), rep(5,20)) weights = runif(100, 0, 1) mydata = data.frame(response,group,weights) ## run summaryBy without weights:

Full_Name: Marc Paterno Version: 2.9.2 OS: Mac OS X 10.5.8 Submission from: (NULL) (99.53.212.55) summaryBy() produces incorrect results when given some data frames. Below is a transcript of a session showing the result, in a data frame with 2 observations of 2 variables. ------------------- thomas:999 paterno$ R --vanilla R version 2.9.2 (2009-08-24) Copyright (C) 2009 The R Foundation for

Hi: I have attempted to following some instructions to use --link-dest in order to preserve space for multiple backups. I'm using rsync on Cygwin with a NAS (ext4) which does support hard-links on the filesystem. I've written a short program that does attempt to create a hard-link on this NAS from Cygwin and it does look to be working. If I run ls -li on the NAS the inodes are the same.

Hi, since I have quite large tables and the processing takes quite a while I am curious if I can improve the performance of this aggregation somehow: At the moment I am using summaryBy from the doBy package under R 2.4.0, Win2K. summaryBy(soc_s6aq5 + soc_s6aq7 + soc_s6aq9 + soc_s6aq11 ~ hh + comgroup,soc6a,postfix=c("","","",""),FUN=sum, na.rm=T) The

I'm trying to use a self-written function with the summaryBy function (doBy package). I have lots of data from Monte Carlo experiments comparing different estimators across different (combinations of) parameter values, similar to the following form: colnames(mydata) <- c("X", "b0", "b1", # parameter combination, corresponding (true) parameter values

The R script below gives values of 1 for all minimum values when I use a custom function in summaryBy. I get the correct values when I use FUN=min directly. Any help is much appreciated. The continuous information provided in this forum is fabulous as are the different R packages available. Rene # Simulated simplified data Subj <- rep(1:4, each=6) Analyte <-

Please use an informative subject for sake of the archives. Here are several solutions: aggregate(DF[4:8], DF[2], mean) library(doBy) summaryBy(x1 + x2 + x3 + x4 + x5 ~ name, DF, FUN = mean) # if Exp, name and id columns are factors then this can be reduced to library(doBy) summaryBy(. ~ name, DF, FUN = mean) library(reshape) cast(melt(DF, id = 1:3), name ~ variable, fun = mean) On

Wow.. thanks for the deluge of responses! Aggregate seems like the way to go here. But, suppose that instead of integers in column V2, I actually have dates (and instead of keeping the minimum integer, I want to keep the earliest date): > df =

I don't see the problem with the following... the citations and baseball data work fine, but my simulated data seems to give BTm a headache. What am I missing? --- library(BradleyTerry) library(doBy) ng <- 100 players <- factor( sort( c( "jeff", "mike", "paul", "rich" ) ) ) np <- length( players ) p1 <- factor( c( rep( "jeff", ng )

I large datset that includes subjects(ID), Dates and events that need to be counted.  Not every date includes an event, and I need to only count one event per 30days, per subject.  So in essence, I need to create a 30-day "black out" period during which time an event cannot be "counted" for each subject.  The reason is that a rule has been set up, whereby a subject can only be

Hello all, I really appreciate how helpful the people in this list are. Would it be too much to ask to send a small script to have it peer-reviewed? to make sure I am not making blatant mistakes? The script takes an experiment.dat as input and generates system Throughput using ggplot2. It works now ... [sigh] but I have this nasty feeling that I might be doing something wrong :). Changing

Hello, struggling with the very basic needs... :( any help appreciated. #using the package doBY #who drinks how much beer per day and therefor cannot calculate rowise maxvals evaluation=data.frame(date=c(1,2,3,4,5,6,7,8,9), name=c("Michael","Steve","Bob", "Michael","Steve","Bob","Michael","Steve","Bob"),

Me: Win XP 4 gig ram R 2.9.2 library(foreign) # to read/write SPSS files library(doBy) # for summaryBy library(RODBC) setwd("C:\\Documents and Settings\\............00909BR") gc() memory.limit(size=4000) ## PROBLEM: I have memory limit problems. R and otherwise. My dataframes for merging or subsetting are about 300k to 900k records. I've had errors such as vector size too large.

Hi, Try either: tolerance <- read.csv("http://www.ats.ucla.edu/stat/r/examples/alda/data/tolerance1.txt") ?aggregate(exposure~male,data=tolerance,mean) ?# male exposure #1??? 0 1.246667 #2??? 1 1.120000 #or ?library(plyr) ?ddply(tolerance,.(male),summarize,exposure=mean(exposure)) #? male exposure #1??? 0 1.246667 #2??? 1 1.120000 #or

Dear users, By running the script below, R crashes systematically at the last command, namely dev.off(), on Windows 7, but not on Windows XP. I therefore don't provide a reproducible example and do not really extract the relevant parts of the script because it has most likely nothing to do with the script itself. I can do it though if you think it might be relevant. R crashes on Windows