similar to: confused by classes and methods.

Hello, We are having some strange issues with RODBC related to integer columns. Whenever we do a sql query the data in a integer column is 150 actual data points then 150 0's then 150 actual data points then 150 0's. However, our database actually has numbers where the 0's are filled in. Furthermore, other datatypes do not have this problem: double and varchar are correct and do not

Hello, Is there a way to find where a script is located within a script? getwd() doesn't do what I want because it depends on where R was called from. I want something like source("randomFile") and within randomFile there is a function called whereAmI() which returns c:\blah\blah2\randomFile.R In perl there is a library called FindBin and $FindBin::Bin has the directory of the file

Hello all, I've scoured the RODBC.pdf, but there appears to be no way to set the name of the RODBC connection. This is useful for the DBA's to know that some processes should only run for so long and can be automatically killed. But currently the name is just R. so they aren't sure if the connection can be automatically killed. We are able to set this with our perl ODBC interfaces

Hi everyone, I have the following code that works in data frames taht I would like tow ork in data.tables . However, I'm not really sure how to go about it. I basically have the following names = c("data1", "data2") frame = data.frame(list(key1=as.integer(c(1,2,3,4,5,6)), key2=as.integer(c(1,2,3,2,5,6)),data1 = c(3,3,2,3,5,2), data2= c(3,3,2,3,5,2))) for(i in

Hi, This has bugged me for a bit. First question is how to keep classes with rbind, and second question is how to properly return vecotrs instead of lists after turning an rbind of lists into a data.frame list1=list(a=2, b=as.Date("20090102", format="%Y%m%d")) list2=list(a=2, b=as.Date("20090102", format="%Y%m%d")) rbind(list1, list2) #this loses the

Dear R users, I am sorry to disturb you! But I really need your help for the usage of sigPathwy. Actually, I want a sliding window analysis for possible chromosome expression pattern mining. My research microorganism is a plant pathogen, Gibberella zeae, and I first used SAS to divide locus number with 10, 20, 30, or 40 on the fungal chromosome according to their location. I really

So I have a function that does lapply's for me based on dimension. Currently only works for length(pivotColumns)=2 because I haven't fixed the rbinds. I have two versions. One runs WAYYY faster than the other. And I'm not sure why. Fast Version: fedb.ddplyWrapper2Fast <- function(data, pivotColumns, listNameFunctions, ...){ lapplyFunctionRecurse <- function(cdata, level=1,

Hi, Although my doubt is pretty,as i m not from stats background i am not sure how to proceed on this. Currently i am doing a forecasting.I used ARIMA to forecast and time series was volatile i used garchFit for residuals. How to use the output of Garch to correct the forecasted values from ARIMA. Here is my code: ###delta is the data fit<-arima(delta,order=c(2,,0,1)) fit.res <-

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

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

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 >

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

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

?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 >

Hi, I have a dataframe with some 800 rows and 14 columns. Could you please advise how I can concatenate the rows - one after another. Similarly for columns, one below the other. Many thanks. Cheers, Santana [[alternative HTML version deleted]]

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

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)

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

Hi Vijay Thanks for your quick response. I am using gluster 3.8.11 on Centos 7 servers glusterfs-3.8.11-1.el7.x86_64 clients are centos 6 but I tested with a centos 7 client as well and results didn't change gluster volume info Volume Name: atlasglust Type: Distribute Volume ID: fbf0ebb8-deab-4388-9d8a-f722618a624b Status: Started Snapshot Count: 0 Number of Bricks: 5 Transport-type: tcp