similar to: Conditionally adding a constant

Hi, I always have a question about how to do this best in R. I have a data frame and a set of criteria to filter points out. My procedure is to always locate indices of those points, check if index vector length is greater than 0 or not and then remove them. Meaning dftest <- data.frame(x=rnorm(100),y=rnorm(100)); qtile <- quantile(dftest$x,probs=c(0.05,0.95)); badIdx <- which((dftest$x

AdvisoRs: Is the following a bug, feature, hinky error message, or dumb Bert? > mtest <- matrix(1:12,nr=4) > dftest <- data.frame(mtest) > ix <- cbind(1:2,2:3) > mtest[ix] <- NA > mtest [,1] [,2] [,3] [1,] 1 NA 9 [2,] 2 6 NA [3,] 3 7 11 [4,] 4 8 12 ## But ... > dftest[ix] <- NA Error in `[<-.data.frame`(`*tmp*`, ix, value

Hello, I am pretty new to R, I have always used SAS and SAS products. My target variable is binary ('Y' and 'N') and i have about 14 predictor variables. My goal is to compare different variable selection methods like Forward, Backward, All possible subsests. I am using misclassification rate to pick the winner method. This is what i have as of now, Reg <- glm (Graduation ~.,

Dear baseRs, I recently made a mistake when renaming data frame columns, accidentally creating an NA column. I found the following strange behavior when negative indexes are used. Can anyone explain what happens here. No "workarounds" required, just curious. Dieter Version: Windows, R version 2.6.1 (2007-11-26) #----------------------------- df = data.frame(a=0:10,b=10:20) df[,-2]

Hi there, I have a list of dataframes (generated by reading multiple files) and all dataframes are comparable in dimension and column names. They also have a common column, which, I'd like to use for merging. To give a simple example of what I have: df1 <- data.frame(c(LETTERS[1:5]), c(2,6,3,1,9)) names(df1) <- c("pos", "data") df3 <- df2 <- df1 df2$data

Dear expeRts, What is the best approach to create a third data frame from two given ones, when the new/third data frame has last column computed from the last columns of the two given data frames? ## Okay, sounds complicated, so here is an example. Assume we have the two data frames: df1 <- data.frame(Year=rep(2001:2010, each=2), Group=c("Group 1","Group 2"), Value=1:20)

Hey Folks, Could somebody show me how to loop through a list of dataframes? I want to be able to generically access their elements and do something with them. For instance, instead of this: df1<- data.frame(x=(1:5),y=(1:5)); df2<- data.frame(x=(1:5),y=(1:5)); df3<- data.frame(x=(1:5),y=(1:5)); plot(df1$x,df1$y); plot(df2$x,df2$y); plot(df3$x,df3$y); I would like to do something like:

Hi, i'm very new to R, so sorry for what i'm sure is a very basic question. I'm producing a boxplot with the data below: df3<-data.frame( x=c(10,11,115,12,13,14,16,17,18,21,22,23,24,26,27,28,29,3,30,32,33,34,35,4,4 1,45,5,50,52,56,58,6,67,6738,68,7,8,9), fq=c(8,11,1,2,4,4,2,2,6,3,4,2,2,1,1,1,4,51,3,1,1,1,1,35,1,1,19,2,1,1,1,14,1, 1,1,10,13,5),

Dear group, Here is my df : df3 <- structure(list(DESCRIPTION = c("COPPER May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SUGAR NO.11 Jul/10", "SUGAR NO.11 May/10", "WHEAT Jul/10", "SPCL HIGH GRADE ZINC USD",

Simple illustration, > df3 <- data.frame(id=c(3,2,1,4), age=c(40,50,60,50), dose1=c(1,2,1,2), dose2=c(2,1,2,1), dose4=c(3,3,3,3))> df3 id age dose1 dose2 dose41 3 40 1 2 32 2 50 2 1 33 1 60 1 2 34 4 50 2 1 3> melt.data.frame(df3, id.var=1:2, na.rm=T) id age variable value1 3 40 dose1 12 2 50 dose1 23 1

Hello, My problem is that I would like to merge multiple files with a common column but merge accepts only two data.frames to merge. In the real situation, I have 26 different data.frames with a common column. I can of course use merge many times (see below) but what would be more sophisticated solution? For loop? Any ideas? DF1 <- data.frame(var1 = letters[1:5], a = rnorm(5)) DF2 <-

Hallo Everyone I have the kind of problem that one should never have because one must always plan well and communicate with your team. But now I haven't so here is my problem. I have data coming in on a daily basis from surveys in 10 towns. The questionnaire has 62 variables but some of the regions have used older versions of the questionnaire that have a few variables less. I want to combine

write.table with large data frames takes quite a long time > system.time({ + write.table(df, '/tmp/dftest.txt', row.names=FALSE) + }, gcFirst=TRUE) user system elapsed 97.302 1.532 98.837 A reason is because dimnames is always called, causing 'anonymous' row names to be created as character vectors. Avoiding this in src/library/utils, along the lines of Index:

Hello ... Are there any known problems or even gotchas to look out for when using a gzfile connection in read.csv/read.table in Windows? In the package PROcess, available at www.bioconductor.org/repository/devel/package/html/PROcess.html there are two files in the PROcess/inst/Test directory which are of the extension *.csv.gz. With both files, if I open up a gzfile connection, say: vv <-

Hi all, I have dataframe that was created from the fusion of two dataframes. Both spanned over the same time intervall but contained different information. When I put them together, the info overlapped since there is no holes in the time interval of one of the dataframe. Here is an example where the rows "sp=A and B" are part of a first df and the rows "sp=C" come from a

I have a series of data frames that are identical structurally, i.e. - made with the same code, but I need to add them together so that they become one, longer, data frame, i.e. - each of the slot vectors are increased in length by the length of the added data frame vectors. So if I have df1 with a slot A so that length(df1$A) = 100 and I have df2 with a slot A so that length(df2$A)=200 then I

R Users, I am new to R and have tried to figure out how to automate this process instead of using excel. I have read in this dataframe into r with read.table. I need to reshape the data from the first table into the format of the second table. TractID StandID Species CruiseDate DBHClass TreesPerAcre Carbon Stand 1 Loblolly Pine 5/20/2010 10 1.2 Carbon Stand 1 Loblolly Pine

Hi everybody. I'll first explain my problem and what I'm trying to do. Admit this example: I'm working on 5 different weather stations. I have first in one file 3 of these 5 weather stations, containing their data. Here's an example of this file: DF1 <- data.frame(station=c("ST001","ST004","ST005"),data=c(5,2,8)) And my two other stations in

I have the following data: prefix <- c("cheap", "budget") roots <- c("car insurance", "auto insurance") suffix <- c("quote", "quotes") prefix2 <- c("cheap", "budget") roots2 <- c("car insurance", "auto insurance") roots3 <- c("car insurance", "auto

Hello R user, I have several data frames with >100 columns and I did a linear regression over time of each column df1.lm <- lapply(df1, function(x) lm(x~year)$coeff[2]) that worked fine and I get slope of each column oder time - until I divided df1 by df2 df3 <- df1/df2 > df3.lm <- lapply(df3, function(x) lm(x~year)$coeff[2]) Error in lm.fit(x, y, offset = offset, ...) :