search for: mydata2

R helpers I am getting to grips with R but came across a small problem today that I could not fix by myself. I have 3 text files, each with a single column of data. I read them in using: myData1<-scan("C:/Program Files/R/myData1.txt") myData2<-scan("C:/Program Files/R/myData2.txt") myData3<-scan("C:/Program Files/R/myData3.txt") I wanted to produce a chart with 3 boxplots of the data and used: boxplot(myData1, myData2, myData3) This worked fine so I consulted R [help(bxp)] to add some format and labels e.g....

Dear all, I have problem when reading a table into R. The total row of read in table has is much less than the original saved table. I built a 1,273,230 by 6 data set named "mydata2", it was saved in the following command, write.table(mydata2, "mydata2.txt", row.name=F,col.name=T,quote=F,sep="\t") The next day I read in above saved text file into R, temp<-read.table("mydata2.txt",header=T,sep="\t",na.strings="NA") H...

you could try mapply mydata2<-mapply("[", mydata, lapply(mydata, function(x) !x %in% A)) mydata2[[1]]<-A #to replace the obviously deleted elements of "A" mydata2 mydata2[[1]] mydata2[[2]] mydata2[[3]] mydata2[[4]] Stefano -----Messaggio originale----- Da: r-help-bounces at stat.math.ethz.ch...

Hello, does anyone know of a quick way to create a data frame "like" another, but with more rows? What I'd like to do is this: if mydata is a data.frame like a b c 1 TRUE yes 2 FALSE no 3 TRUE yes I'd like to get mydata2 with the same column names and column types, but without the values and with more rows. All I could think of was to manually do mydata2 <- maydata, then repeat mydata2 <- rbind(mydata2, mydata2) until mydata2 is long enough, then cut to desired length and overwrite with new data. Not exactly...

...t the moment it is omitted). So I would expect to get a dataframe with 1000 rows some of which would be empty, but instead I get a dataframe with 995 rows. In this case missing 5 rows were omitted. Any suggestions? Thanks, Olga ---------------- result<-list() for(i in 1:1000)try({ hclass<-mydata2$tclass[mydata2$tspecies%in%com[[i]][[5]][[1]]] horder<-mydata2$torder[mydata2$tspecies%in%com[[i]][[5]][[1]]] hfamily<-mydata2$tfamily[mydata2$tspecies%in%com[[i]][[5]][[1]]] hgenus<-mydata2$tgenus[mydata2$tspecies%in%com[[i]][[5]][[1]]] hspecies<-mydata2$tspecies[mydata2$tspecies%in%co...

Hello I have dataframes. mydata1 <-data.frame(value=c(15,20,25,30,45,50),dates=c("2005-05-25 07:00:00 ","2005-05-25 19:00:00","2005-06-25 07:00:00","2005-06-25 19:00:00 ","2005-07-25 07:00:00","2005-8-25 19:00:00")) or mydata2 <-data.frame(value=c(15,20,25,30,45,50),dates=c("2005-05-25 00:00:00 ","2005-05-25 00:10:00","2005-05-25 00:30:00","2005-05-25 00:40:00 ","2005-05-25 00:50:00","2005-5-25 01:10:00")) I have to get such dataframes mydata1 <-data.fr...

...z",1:8,sep="") mydata$pos<-factor(NA,levels=posl) n=nrow(mydata) mydata$pos<-replicate(n,sample(posl,1,prob=c(0.05,0.05,0.05,0.4,0.3,0.05,0.05,0.05)))#strong preference for z3 and z4 ##pre-treatment of the above row data, number of time (out of 21) each position was observed mydata2=ddply(mydata,.(sub,per,pos),summarize,nobs=length(pos),.drop=F) mydata2[,1:3]=catcolwise(function(x)as.factor(x))(mydata2) summary(mydata2) # boxplot of frequencies of occpupancy require(ggplot2) mydata2$fobs=mydata2$nobs/21 ggplot(mydata2)+geom_boxplot(aes(pos,fobs)) ###chi2 test nobsT=ddply(myd...

I can run one-sample t-test on an array, for example a matrix myData1, with the following apply(myData1, 2, t.test) Is there a similar fashion using apply() or something else to run 2-sample t-test with datasets from two groups, myData1 and myData2, without looping? TIA, Gang

Dear all, I have problem when reading a table into R. The total row of read in table has is much less than the original saved table. I built a 1,273,230 by 6 data set named "mydata2", it was saved in the following command, write.table(mydata2, "mydata2.txt", row.name=F,col.name=T,quote=F,sep="\t") The next day I read in above saved text file into R, temp<-read.table("mydata2.txt",header=T,sep="\t",na.strings="NA") H...

Hi, I have a problem. Please, look at example and try to help me!! > A<-c("aaa","bbb","ccc","ddd","eee") > B<-c("vvv","ooo","aaa","eee","zzz","bbb") > C<-c("sss","jjj","ppp","ddd") > D<-c("bbb","ccc")

...ase - are all the columns in a database considered "vectors" and that they can be operated on individually Therefore I've tried the following mydata <- as.numeric(mydata$apples) when i then look at mydata again the named column is still in "character" format if i do mydata2 <- as.numeric(mydata$apples) the new object mydata2 is empty. Am i missing something about the structure of R? alina [[alternative HTML version deleted]]

Hi all, I am trying to understand Writing R Extension... Section 1.1.5, data: I include two datasets in a package, one using 'save', the other using 'write.table': --- 8< ---- myData1 <- data.frame(x=1:10) write.table(myData1,file="myData1.txt") myData2 <- data.frame(x=2:10) save(myData2,file="myData2.Rdata") --- 8< ---- Then R CMD check aks me to document myData1, but does not ask me to document myData2. In the R session, after 'library(myPack)', the data 'myData2' is automatically present in the session while myD...

...------------. 2) Import the Spss Data in R. Via Hmisc or foreign - both work fine. #import Spssdata in R spssfile <- "C:/tmp/test.sav" #via Hmisc library(Hmisc) Signs <- c("_") mydata1 <- spss.get(spssfile,lowernames=TRUE, allow=Signs) #via foreign library(foreign) mydata2 <- read.spss(spssfile,use.value.labels=TRUE, max.value.labels=Inf, to.data.frame=TRUE) #freq in r describe(mydata1) describe(mydata2) *-----------------------------------------------------------------------------------------. Have a look at the two variables age and sport. In spss the values...

...05,0.05,0.05)))#strong preference for z3 and z4 mydata$pos[mydata$pre=="p"]=replicate(n,sample(posl,1,prob=c(0.3,0.4,0.05,0.05,0.05,0.05,0.05,0.05)))#strong preference for z1 and z2 summary(mydata) # number of time (out of 21) each position was observed, given hab, pre, sub and per mydata2=ddply(mydata,.(hab,pre,sub,per,pos),summarize,nobs=length(pos),.drop=F) mydata2[,1:5]=catcolwise(function(x)as.factor(x))(mydata2) summary(mydata2) # boxplot of frequencies of occpupancy require(ggplot2) ggplot(mydata2)+geom_boxplot(aes(pos,I(100*nobs/21)))+facet_grid(pre~hab) [[alternative...

...ning: X <- as.dist(Y) and I can happily now run either hclust(X) or agnes(X). So that the various bits of output are labelled correctly I would dearly like to be able to give names to the columns and rows of X, as would happen if I ran: mydata<-read.table("clipboard",header=T) mydata2<-t(mydata) mydists<-dist(mydata2) Many thanks for your help. Best wishes, Kris Lockyear.

...fv = c(47068.1437773483, 43743.8087431582, 40323.5209129239, 23420.9455581495, 29382.6947428651, 50460.2202192311, 21810.1456510625, 41747.6053810881)), .Names = c("species", "fruit", "Asfc", "Tfv"), row.names = c(NA, 8L), class = "data.frame") mydata2 <- mydata1[!(mydata1$species %in% c("thgel","alsen")),] mydata3 <- mydata1[!(mydata1$species %in% c("thgel","alsen","poabe")),] mydata_list <- list(mydata1=mydata1, mydata2=mydata2, mydata3=mydata3) #function for regression library(WRS) fo...

...e('treatments'=gl(4,20), 'value'=rpois(80, 1)) model1 <- glm(value ~ treatments, data=mydata1, family=poisson) means1 <- with(mydata1, tapply(value, treatments, mean)) now I need the confidence intervals for the means And then again for a negative binomial GLM require(MASS) mydata2 <- data.frame('treatments'=gl(4, 4, 64, LETTERS[1:4]), 'species'=gl(4, 1, 64, letters[1:4]), 'value'=rnegbin(64,1,1)) model2 <- glm.nb(value ~ treatments*species, data=mydata2) means2 <- with(cbind('x'=gl(16,4),mydata2), tapply(value, x, mean)) Can I get th...

Hello fellow R's, I?ve been learning to use the ggplot2 library, and after a full day of work I still have a couple of basic questions. Here is an example: mydata=data.frame(x=runif(20),y=runif(20),n=runif(20)) mydata2=data.frame(x=c(0.4,0.6,0.5),y=c(0.4,0.4,0.6)) ggplot(mydata, aes(x, y)) + geom_point(aes(size = n)) + geom_polygon(data=mydata2,aes(x,y,alpha=0.5)) In this plot, the points are labeled as "n" (the name of the variable) and the polygon is labeled as "0.5" (the alpha value us...

...="cv.aic", data=mydata) summary(bandwidth) # perform nonparametric regression using bandwidth results <- npreg(bws=bandwidth) summary(results) # use plot to plot results plot(results,view="fixed",theta=300) # example 2: restrict data to observations for which x1>=x2 mydata2 <- mydata[mydata$x1>=mydata$x2,] # calculate bandwidth bandwidth2 <- npregbw(formula=y ~ x1 + x2, regtype="ll", bwmethod="cv.aic", data=mydata2) summary(bandwidth2) # perform nonparametric regression using bandwidth2 results2 <- npreg(bws=bandwidth...

...fv = c(47068.1437773483, 43743.8087431582, 40323.5209129239, 23420.9455581495, 29382.6947428651, 50460.2202192311, 21810.1456510625, 41747.6053810881)), .Names = c("species", "fruit", "Asfc", "Tfv"), row.names = c(NA, 8L), class = "data.frame") mydata2<- mydata1[!(mydata1$species %in% c("thgel","alsen")),] mydata3<- mydata1[!(mydata1$species %in% c("thgel","alsen","poabe")),] mydata_list<- list(mydata1=mydata1, mydata2=mydata2, mydata3=mydata3) library(WRS) foo_reg<- function(dat, xva...