similar to: aggregation with extra columns

I have a frame which contains 3 columns: "date" "defectnum" "state" And I want to get the most recent state change for a given defect number. date is POSIXct. I have tried: aggregate(ev$date, by=list(ev$defectnum), max) Which appears to be working except that the dates seem to come back as integers (presumably the internal representation of POSIXct). When I

Thanks to those who pointed me at the solutions to the legend overprinting the bars. I took the "easy" way of rescaling the y axis, picking the scaling factor for stacked bars is somewhat problematic but sufficient for my application. I have another couple of barplot questions: - Can I extend the major ticks on the Y axis across the page? Or both axes to form a grid? - A really

I know enough about R to be dangerous and our marketing people have asked me to "automate" some reporting. Data comes from an SQL source and graphs and various summaries are currently created manually in Excel. The raw information is invoicing records and the reporting is basically summaries by customer, region, product line etc. With function such as aggregate(), hist() and pareto()

Is length(unique()) what you are looking for? Andy > From: Christoph Lehmann > > Hi I have a question concerning aggregation > > (simple demo code S. below) > > I have the data.frame > > id meas date > 1 a 0.637513747 1 > 2 a 0.187710063 2 > 3 a 0.247098459 2 > 4 a 0.306447690 3 > 5 b 0.407573577 2 > 6 b

I have a data frame and I would like to reshape it to wide format while at the same time applying different aggregate functions to each column AND at times multiple aggregate functions:   test1 = data.frame(         id = c(rep('101',8),rep('102',8)),         phase  = rep(c('D','D','L','L'),4),         day =

Dear useRs We have a data-set (comma delimited) with 12Millions of rows, and 5 columns (in fact many more, but we need only 4 of them): id, factor 'a' (5 levels), factor 'b' (15 levels), date-stamp, numeric measurement. We run R on suse-linux 9.1 with 2GB RAM, (and a 3.5GB swap file). on average we have 30 obs. per id. We want to aggregate (eg. sum of the measuresments under

I have been using ddply to do aggregation, and I frequently define a single aggregation function that I use to aggregate over different groups. For example, require(plyr) dat <- data.frame(x = sample(3, 100, replace=TRUE), y = sample(3, 100, replace = TRUE), z = rnorm(100)) f <- function(x) { data.frame(mean.z = mean(x$z), sd.z = sd(x$z)) } ddply(dat, "x", f) ddply(dat,

Dear Developers, Having spent time developing and thinking about how data aggregation and summary statistics can be enhanced in R, I would like to present my ideas/efforts in the form of two commands: The first, which for now I called 'collap', is an upgrade of aggregate that accommodates and extends the functionality of aggregate in various respects, most importantly to work with

Dear R experts, I am currently facing a tricky problem which I have read a lot about in the various R mailing lists without finding exactly what I need. I have a big data frame DF (about 2,000,000 rows) with 7 columns being variables and 1 being a measure (using reshape package nomeclature). There are no "duplicates" in it. Fot each of the variables I have some "rules" to

I've been inspired to look at the R source code by some strange timing results that I wrote about on my blog at radfordneal.wordpress.com (see the posts on "Speeding up parentheses..." and "Two surprising things...". I discovered that the strange speed advantage of curly brackets over parentheses is partially explained by an inefficiency in the evalList and

Hello, Sandro! On 11.05.2018 12:19, Sandro Bonazzola wrote: > Sadly, the new qemu-kvm-ev we prepared for CentOS 7.5 didn't get released ( > https://bugs.centos.org/view.php?id=14764) but the new build is ready. After installing CentOS 7.5 and installing package qemu-kvm-ev I can't install KVM on x86_64 arch: command "yum -y install perf qemu-kvm-ev qemu-kvm-tools-ev

I have a set of evaluation variables (n) for each sample (sample size is large enough) and I am trying to use R (nnet package) to aggregate the data. However, I don't know the weight for each variable (I am sure the weight shouldn't be equally assigned). Specifically, I have 12 indices (CO2, SO2, TSP...) for 100 cities and I want to calculate weight for each and finally obtain a

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

Sandro, Could you please enumerate the actual technical differences between stock qemu-kvm and qemu-kvm-ev? For example, what could one do with qemu-kvm-ev that cannot with qemu-kvm? Lucian -- Sent from the Delta quadrant using Borg technology! Nux! www.nux.ro ----- Original Message ----- > From: "Sandro Bonazzola" <sbonazzo at redhat.com> > To: "Discussion about

Dear all, I do not seem to grasp how contrasts are set for ordered factors. Perhaps someone can elighten me? When I work with ordered factors, I would often like to be able to reduce the used polynomial to a simpler one (where possible). Thus, I would like to explicetly code the polynomial but ideally, the intial model (thus, the full polynomial) would be identical to one with an ordered factor.

Hi, I am new to R. I don't have strong background of statistics. I am a student of Geotechnical Engineering. I tried to run a nonlinear regression for a three-variable function, that is N = f(CSR, ev) # N is a function of CSR and ev, and N = CSR/(A +B*CSR), wherer (A,B) are function of ev. N, CSR and ev are observed in the experiments. Following is my R script. rm(list=ls())

With this set-up options(warn = 1) tf <- tempfile() finalizer <- function(obj) { message("finalizer") close(obj$f) } this code works ev <- new.env() ev$f <- file(tf, "w") reg.finalizer(ev, finalizer) rm(ev) gc() whereas this (reversing the order of file() and reg.finalizer()) ev <- new.env() reg.finalizer(ev, finalizer) ev$f <- file(tf,

host static anyterm content locally, url parameterize anyterm rows/cols/general param update spec/makefile Ideally I wanted and tried hard to put all this into a seperate ovirt-server--anyterm subpackage, but we cannot 'reopen' the ovirt server virtual host defined in ovirt-server.conf to add the neccessary rewrite rules. it would be nice to figure out a way to do this ---

Hello When I read a SPSS *.por file with read.spss everything after a umlaut is missing: > library("foreign") > spssdaten <- read.spss("projets.por") > attr(spssdaten$PROJETX, "value.labels")[1:20] Bg Stammzellenforschung Bb 863 862 Bb

> > Hello All, > Please help me with this problem.I have been having this problem for over a month now and I could not find any information.I later realised that error is with MATRIX package. I am working on graph object using IGRAPH version 0.5.2-2 package & wanted to do Bonacich Power. What I have is undirected GRAPH. This is my graph object. The file 'Bonacich