similar to: Identify first row of each ID within a data frame, create a variable first =1 for the first row and first=0 of all other rows

John, Thanks for enlightening us so we better understand. I won't argue with your wish to learn to do things in base R first. I started that way, myself, and found lots of the commands not particularly easy to fit into a single worldview. Many functions I read about were promptly forgotten, especially those without great documentation and not enough examples of real world usage. This is why

Dear R help folks, First my apologizes for sending several related questions to the list server. I am trying to learn how to manipulate data in R . . . and am having difficulty getting my program to work. I greatly appreciate the help and support list member give! I am trying to write a program that will run through a data frame organized by ID and for the first line of each new group of data

Rui: "f these two, diff is faster. But of all the solutions posted so far, Ben Bolker's is the fastest." But the explicit version of diff is still considerably faster: > D <- c(rep(1,10),rep(2,6),rep(3,2)) > microbenchmark(c(1L,diff(D)), times = 1000L) Unit: microseconds expr min lq mean median uq max neval c(1L, diff(D)) 3.075 3.198 3.34396

?s 16:30 de 27/11/2024, Sorkin, John escreveu: > I am an old, long time SAS programmer. I need to produce R code that processes a dataframe in a manner that is equivalent to that produced by using a by statement in SAS and an if first.day statement and a retain statement: > > I want to take data (olddata) that looks like this > ID Day > 1 1 > 1 1 > 1 2 > 1 2 > 1 3 >

On 11/27/24 08:30, Sorkin, John wrote: > I am an old, long time SAS programmer. I need to produce R code that processes a dataframe in a manner that is equivalent to that produced by using a by statement in SAS and an if first.day statement and a retain statement: > > I want to take data (olddata) that looks like this > ID Day > 1 1 > 1 1 > 1 2 > 1 2 > 1 3 > 1 3 >

Was wondering when this would be suggested. But the question was about getting the final dataframe... newdta <- olddta newdta$FirstDay <- ave(newdata$date, newdata$ID, FUN = \(x) x[1L]) On November 27, 2024 11:13:49 AM PST, Rui Barradas <ruipbarradas at sapo.pt> wrote: >?s 16:30 de 27/11/2024, Sorkin, John escreveu: >> I am an old, long time SAS programmer. I need to

Check out the dplyr package, specifically the mutate function. # Create new column based on existing column value df <- df %>% mutate(FirstDay = if(ID = 2, 5)) df Repeat as needed to capture all of the day/firstday combinations you want to account for. Like everything else in R, there are probably at least a dozen other ways to do this, between base R and all of the library packages

I am an old, long time SAS programmer. I need to produce R code that processes a dataframe in a manner that is equivalent to that produced by using a by statement in SAS and an if first.day statement and a retain statement: I want to take data (olddata) that looks like this ID Day 1 1 1 1 1 2 1 2 1 3 1 3 1 4 1 4 1 5 1 5 2 5 2 5 2 5 2 6 2 6 2 6 3 10 3 10 and make it look like this: (withing each

Hello! I have a data frame with dates. I need to create a new "month" that starts on the 20th of each month - because I'll need to aggregate my data later by that "shifted" month. I wrote the code below and it works. However, I was wondering if there is some ready-made function in some package - that makes it easier/more elegant? Thanks a lot! # Example data:

Hi - I am trying to find and describe missing data in a time series. For instance, in the library openair, there is a data frame called "mydata": library(openair) head(mydata) date ws wd nox no2 o3 pm10 so2 co pm25 1 1998-01-01 00:00:00 0.60 280 285 39 1 29 4.7225 3.3725 NA 2 1998-01-01 01:00:00 2.16 230 NA NA NA 37 NA NA NA 3 1998-01-01 02:00:00

I am trying to use the cca/rda/capscale functions in vegan to analyse genetic distance data ( provided as a dist object calculated using dist.genpop in package adegenet) with geographic distance partialled out ( provided as a distance object using dist function in veganthis method is attempting to follow the method used by Geffen et al 2004 as suggested by Legendre and . FORTIN (2010). I

Hi all -- I am working on 64-bit Windows XP. I'm not a very technical person when it comes to the command line stuff, so please forgive me if this is a stupid question. I have a bunch of HDF files, and I want to dump a single PM25 data layer from each file to .txt by invoking ncdump.exe from system(). Here's a sample command string: "C:/ncdump -v PM25 C:/01aug2010.hdf >

Hi, This is my code (my data is attached): library(languageR) library(rms) library(party) OLDDATA <- read.csv("/Users/Abigail/Documents/OldData250412.csv") OLDDATA$YD <- factor(OLDDATA$YD, label=c("Yes", "No"))? OLDDATA$ND <- factor(OLDDATA$ND, label=c("Yes", "No"))? attach(OLDDATA) defaults <- cbind(YD, ND) set.seed(47) data.controls

Hi Kostas, The function vectorField in the plotrix package may do what you want. See the example. Jim On Tue, Jul 25, 2023 at 9:30?PM konstantinos christodoulou <konstantinos.christodoulou1 at gmail.com> wrote: > > Dear Rcommunity, > > I hope this email finds you well. I am writing to seek your assistance with > a data visualization problem I am facing while working with R.

My data frame shows changes on the variable act which records the consecutive duration (in seconds) of two states (wet-dry) over a few days for several?individuals (identified by Ring). Since I want to work with daytime (i.e. from dawn till dusk) and night time (i.e. from dusk till next dawn), I have to split act in two: from time[i] till dusk and from dusk until time[i+1], and from time[k] till

Isn't anything in a data frame that is not explicitly numeric a *factor*? -Greg > -----Original Message----- > From: Peter Dalgaard BSA [mailto:p.dalgaard@biostat.ku.dk] > Sent: Friday, December 07, 2001 5:32 PM > To: Erich Neuwirth > Cc: r-devel@stat.math.ethz.ch > Subject: Re: [Rd] question > > > Erich Neuwirth

Dear R wizards--- I have a wrapper on mclapply() that makes it a little easier for me to do multiprocessing. (Posting this may make life easier for other googlers.) I pass a data frame, a vector that tells me what rows should be recomputed, and the function; and I get back a vector or matrix of answers. d <- data.frame( id=1:6, val=11:16 ) loc <- c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE)

Dear Rcommunity, I hope this email finds you well. I am writing to seek your assistance with a data visualization problem I am facing while working with R. Problem Description: I have a dataframe named "df" containing the following columns: "longitude", "latitude", "sea_currents_mag", and "sea_currents_direction". The dataframe includes sea

Can you please provide more details about your volume configuration and the version of gluster that you are using? Regards, Vijay On Fri, Jun 9, 2017 at 5:35 PM, mohammad kashif <kashif.alig at gmail.com> wrote: > Hi > > I have just moved our 400 TB HPC storage from lustre to gluster. It is > part of a research institute and users have very small files to big files > ( few

Hi I have just moved our 400 TB HPC storage from lustre to gluster. It is part of a research institute and users have very small files to big files ( few KB to 20GB) . Our setup consists of 5 servers, each with 96TB RAID 6 disks. All servers are connected through 10G ethernet but not all clients. Gluster volumes are distributed without any replication. There are approximately 80 million files in