similar to: Subsetting rows by multiple levels of selected values

Dear all, I wish to generate a lattice boxplot which skips an empty cell in a design. I have trawled r-help, scruitinized xyplot(lattice) help page, and merrily reproduced examples of using skip from a couple of previous r-help queries and the example given in Pinheiro & Bates. But I must be missing something... Here's an example (running R 1.9.1 on Win2k): # generate some data df1

Hi, R-listers, Failed, when I tried to merge df1 and df2 by "codetot" in df1 and "codetoto" in df2. I want to know the reason and how to merge them together. Data frames and codes I have used were listed as followed. Thanks a lot in advance. df1: popcode codetot p3need BCPy01-01 BCPy01-01-1 100.0000 BCPy01-01 BCPy01-01-2 100.0000 BCPy01-01 BCPy01-01-3 100.0000 BCPy01-02

Subsetting from a dataframe with only one variable returns a vector, not a dataframe. This seems somewhat inconsistent. Wouldn't it be better if subsetting would respect the structure completely? v1<-1:4 v2<-4:1 df1<-data.frame(v1) df2<-data.frame(v1,v2) sel1<-c(TRUE,TRUE,TRUE,TRUE) > df1[sel1,] [1] 1 2 3 4 > df2[sel1,] v1 v2 1 1 4 2 2 3 3 3 2 4 4 1 -- Erich

#I want to "merge" or "join" 2 dataframes (df1 & df2) into a 3rd (mydf). I want the 3rd dataframe to contain 1 row for each row in df1 & df2, and all the columns in both df1 & df2. The solution should "work" even if the 2 dataframes are identical, and even if the 2 dataframes do not have the same column names. The rbind.fill function seems to work. For

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)

The rbind on empty and nonempty data frames behaves inconsistently. I am not sure if by design. In the first example, first row is deleted, which may or may not be on purpose: df1 <- data.frame() df2 <- data.frame(foo=c(1, 2), bar=c("a", "b")) rbind(df1, df2) foo bar 2 2 b Now if we continue: df1 <- data.frame(matrix(0, 0, 2)) names(df1) <- names(df2)

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

Hi, I have two dataframes: The first, df1, contains some missing data: cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 The second, df2, contains the following: cola colb colc cold cole 1 1.4 0.8 0.02 1.6 0.6 I'm wanting all missing data in df1$cola to be replaced by the value of df2$cola.

Hello I have 2 data frames DF1 and DF2 where DF2 is a subset of DF1: DF1= data.frame(V1=1:6, V2= letters[1:6]) DF2= data.frame(V1=1:3, V2= letters[1:3]) How do I create a new data frame of the difference between DF1 and DF2 newDF=data.frame(V1=4:6, V2= letters[4:6]) In my real data, the rows are not in order as in the example I provided. Thanks much Joseph [[alternative HTML version

Hello, All: I'm getting strange errors with write.csv with some objects of class c('findFn', 'data.frame'). Consider the following: df1 <- data.frame(x=1) class(df1) <- c('findFn', 'data.frame') write.csv(df1, 'df1.csv') # Error in x$Package : $ operator is invalid for atomic vectors df2 <- data.frame(a=letters[1:2],

HI,   I have searched the R-help achive, trying to find a way to sort columns in a data frame according to a specific list, but not be able to find a general way to do it.   My data frame contains columns, with each one named from a sample ID, and each sample was measured in a specific time, generating one column of data, now I would like to sort the columns according to the time course, so I have

Hello all, I have a quandry I have been scratching my head about for a while. I've searched the manual and the web and have not been able to find an acceptable result, so I am hoping for some help. I have two data frames and I want to index into the first using the second, and replace the specific values I have indexed with more values from the second data.frame. I can do this

Hello, I have two dataframes DF1 and DF2 that should be identical but are not (DF1 has some rows that aren't in DF2, and vice versa). I would like to produce a new dataframe DF3 containing rows in DF1 that aren't in DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1). I have a solution for this problem (see self contained example below) but it's awkward and

Hi, Two ways to create what should normally be the same data frame: > df1 <- data.frame(a=character(0), b=character(0))> df1 [1] a b <0 rows> (or 0-length row.names) > df2 <- as.data.frame(matrix(character(0), ncol=2, dimnames=list(NULL, letters[1:2]))) > df2 [1] a b <0 rows> (or 0-length row.names) unique() works as expected except that I

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 all, probably really simple to solve, but having no background in programming I haven't been able to figure this out: I have two dataframes like df1 <- data.frame(names1=c('aa','ab', 'ac', 'ad'), var1=c(1,5,7,12)) df2 <- data.frame(names2=c('aa', 'ab', 'ac', 'ad', 'ae'), var2=c(3,6,9,12,15)) Now I want merge

I have several data frames, eg: > df1 <- data.frame(x=seq(0,10), y=seq(10,20)) > df2 <- data.frame(a=seq(0,10), b=seq(10,20)) It is common to create loops in R like this: > for(df in list(df1, df2)){ #etc. } This works fine when you know the name of the objects to put into the list. I assume that the order of the objects in the list is respected through the loop. Inside the

I would suggest the method of Sokal and Rholf (1995) S. 498, using the F test. Below I repeat the analysis by Spencer Graves: Spencer: > df1 <- data.frame(x=1:3, y=1:3+rnorm(3)) > df2 <- data.frame(x=1:3, y=1:3+rnorm(3)) > fit1 <- lm(y~x, df1) > s1 <- summary(fit1)$coefficients > fit2 <- lm(y~x, df2) > s2 <- summary(fit2)$coefficients > db <-

Dear Mailing-List, I think this is a newbie question. However, i would like to integrate a loop in the function below. So that the script calculates for each variable within the dataframe df1 the connecting data in df2. Actually it takes only the first row. I hope that's clear. My goal is to apply the function for each data in df1. Many thanks in advance. An example is as follows: df1

This is just a curiosity question. Why do the two different syntaxes for df1 and df2 give such different results in the names(dfx)? Thanks df1 <- data.frame(nas = c("A", "B" , "B" ,"C" ,"B", "A", "D"),nums = c(3, 2, 1, 1, 2, 3, 7)) df2 <- data.frame(nas <- c("A", "B" ,