similar to: Compare two data sets

Is there a way to combine two columns within a data frame? Example data: id snp AL1 AL2 1500 30 A B 1510 30 A A 1520 30 A B This is what I would like: indv snp AL1AL2 1500 30 AB 1510 30 AA 1520 30 AB Any help is greatly appreciated. Alysta

Hi R users I am trying to find unmatched data from two dataframes. I would like to find unmatched data based on several factors. For the following data: dat1 <- data.frame(x = paste("A", 1:6, sep=""), y = c("andy","bob","ciaran","dan", "eion", "fred")) dat1 dat2

Dear all, I have following two list object, both are basically collection of matrices : dat1 <- matrix(rnorm(25*6), ncol=6) dat1 <- split(dat1, seq(5,25,by=5)) dat1 <- lapply(dat1, matrix, ncol=6) dat2 <- matrix(rnorm(25*4), ncol=4) dat2 <- split(dat2, seq(5,25,by=5)) dat2 <- lapply(dat2, matrix, ncol=4) Now I want to replace last 4 columns of each matrix at "dat1"

Hello and thanks for helping. #some data L3 <- LETTERS[1:3] dat1 <- data.frame(cbind(x=1, y=rep(1:3,2), fac=sample(L3, 6, replace=TRUE))) #When x==1 and y==1 I want to replace the 1 values with NA #I can select the rows I want: dat2<-subset(dat1,x==1 & y==1) #replace the 1 with NA dat2$x<-rep(NA,nrow(dat2) dat2$y<-rep(NA,nrow(dat2) #select the other rows and rbind

HI R help, I was trying to get identical data frame from a list using two methods. #Suppose my list is: listdat1<-list(rnorm(10,20),rep(LETTERS[1:2],5),rep(1:5,2)) #Creating dataframe using cbind dat1<-data.frame(do.call("cbind",listdat1)) colnames(dat1)<-c("Var1","Var2","Var3") #Second dataframe conversion

For those who suggest other ways to do this, I ALREADY HAVE ANOTHER DESIGN SOLUTION, DESCRIBED AT THE END. That being said, I want to know if it's possible to reference a slot in an S4 class from another slot, i.e. I'd like to have the "self.*" semantics of Python so that I can reuse a slot. That is, for various reasons it would be nice to be able to do something like:

I need to split a given matrix in a sequential order. Let my matrix is : > dat <- cbind(sample(c(100,200), 10, T), sample(c(50,100, 150, 180), 10, > T), sample(seq(20, 200, by=20), 10, T)); dat [,1] [,2] [,3] [1,] 200 100 80 [2,] 100 180 80 [3,] 200 150 180 [4,] 200 50 140 [5,] 100 150 60 [6,] 100 50 60 [7,] 100 100 100 [8,] 200 150 100 [9,]

Dear list, I have a function whose first argument is '...'. Each element of '...' is a data frame, and there will be at least 2 data frames in '...'. The function processes each of the data frames in '...' and returns a list, whose components are the processed data frames. I would like to name the components of this returned list with the names of the original data

HI, You may try this: dat1<- read.table(text=" CustID TripDate Store Bread Butter Milk Eggs 1 2-Jan-12 a 2 0 2 1 1 6-Jan-12 c 0 3 3 0 1 9-Jan-12 a 3 3 0 0 1 31-Mar-13 a 3 0 0 0 2 31-Aug-12 a 0 3 3 0 2 24-Sep-12 a 3 3 0 0 2 25-Sep-12 b 3 0 0 0 ",sep="",header=TRUE,stringsAsFactors=FALSE) dat2<- dat1[,-c(1:3)] res<- lapply(seq_len(ncol(dat2)),function(i)

HI Fares, You could try this: dat1<- read.table(text=" date????? donation 3jan2003?? 20235 4jan2003?? 25655 5jan2003?? 225860 6jan2003?? 289658 7jan2003?? 243889 8jan2003?? 244338 9jan2003?? 243889 ",sep="",header=TRUE,stringsAsFactors=FALSE) The post is not very specific as to what you need.? I hope this works for you. library(xts)

Hey All, I have a dataset(dat1) like this: ObsNumber ID Weight 1 0001 12 2 0001 13 3 0001 14 4 0002 16 5 0002 17 And another dataset(dat2) like this: ID Height 0001 3.2 0001 2.6 0001

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

Hi, useR- In RMySQL, how do I overwrite records? (equivalent to "replace" query). For example, suppose that dat2 is a newer data.frame than dat1. con <- dbConnect(MySQL()) res <- dbWriteTable(con, "DBname", dat1, row.names=F, append=T, replace=T) res <- dbWriteTable(con, "DBname", dat2, row.names=F, append=T, replace=T) This would not update/replace the

Folks, The projection pursuit regression function in the base R seems to crash when the optimization level is set to zero, i.e. the initial ridge terms are accepted without refitting. I encountered this problem in an out-of-sample prediction exercise using predict. But further investigation suggests the issue is with the ppr fit and predict just sppeds up the crash. The other optlevels seem to be

Let say, I have following matrix : dat <- matrix(rnorm(40), 2, 20) Now I want to partition this like this : dat1 <- dat[1,] dat2 <- dat[2,] But point is that, dat1 and dat2 become vector object. How can I force them to be matrix object with dimension (1x20) ? Thanks, -- View this message in context: http://www.nabble.com/Partitioning-matrix-tp24161021p24161021.html Sent from the R

Hello, Apologies for a similar earlier post. I didn't include enough details in that one. I am having a little trouble subsetting some data based on a grouping variable. I am using an instrument that does depth profiles of a water column. The instrument records on the way down as well as the way up. So thanks to an off-list reply I can subset the data so that all data collected at the

Hi Elisa, I hope this is what you wanted. dat1<-read.csv("peaks.csv",sep=",") #Subset dat2<-dat1[1:5,] res1<-do.call(cbind,lapply(seq_len(nrow(dat2)),function(i) do.call(rbind,lapply(split(rbind(dat2[i,],dat2[-i,]),1:nrow(rbind(dat2[i,],dat2[-i,]))), function(x) {x1<-rbind(dat2[i,],x);

I would be incredibly grateful to anyone who'll help me translate some SAS code into R code. Say for example that I have a dataset named "dat1" that includes five variables: wshed, site, species, bda, and sla. I can calculate with the following SAS code the mean, CV, se, and number of observations of "bda" and "sla" for each combination of

Dear Rxperts! I was wondering if it is possible to write a function which can take in argument of a subset or condition.. Of course, I am aware of the alternate methods like coplot, par.plot, xyplot etc... I am specifically interested in using conditions/subsets with "plot".. A simple fragmented example is shown here.. pltit <- function(y,x,dat,dat1,dat2,sbst) { plot(y~x, data=dat,

Eric: I will try and see if I can figure out the issue by debugging as you suggested. I don?t know why my code after stopifnot is not getting executed where I like the code to run the funlp2 function when the if statement is TRUE but when it is false, I like it to keep running until the stopifnot condition is met. When the stopifnot condition is met, I like to get the output from if statement