search for: unstacking

Hi Everyone, I am trying to understand the unstack() function but after struggling for two days, I have given up. More specifically, I am trying the exercises at the end of Chapter 1 of Data Analysis and Graphics Using R by Maindonald and Braun, 2nd ed. Exercise 18 (p. 41) asks to unstack the Rabbit data frame from the MASS package to get a certain data frame that is shown in the exercise.

I've been reading the R mail archives and I've found a lot of messages with this same kind of problem, but I can't understand the answers. Can one of you try to explain this to me? Here's my example. Given a regression model and a variable, I want to use unstack() on the vector of residuals and make some magic with the result. But unstack hates me. PCSE <- function

...(testdat) > stacked values ind 1 1 X1 2 2 X1 3 3 X1 4 4 X1 5 5 X1 6 1 X2 7 2 X2 8 3 X2 9 4 X2 10 5 X2 11 1 X10 12 2 X10 13 3 X10 14 4 X10 15 5 X10 But the problem I have comes in unstacking, when the order of the columns is changed from the original, to something alphabetical (i.e. X10 goes before X2): > unstacked <- unstack(stacked) > unstacked X1 X10 X2 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 Maintaining the order of columns is very impo...

Folks, I have the following dataframe: > x <- structure(list(name = c("EU B", "EU B", "EU B", "EU B", "EU B", "EU B", "AU A", "AU A", "AU A", "AU A", "AU A", "AU A"), date = c("2010-10-11", "2010-10-12", "2010-10-13",

One would normally want the original order that so that one can stack a list, operate on the result and then unstack it back with the unstacked result having the same ordering as the original. LL <- list(z = 1:3, a = list()) # since we can't do s <- stack(LL,. drop = FALSE) do this instead: s <- transform(stack(LL), ind = factor(as.character(ind), levels = names(LL))) unstack(s)

Hi all, I'm having a problem restructuring my data the way I'd like it. I have data that look like this: Candidate.ID Specialty Office Score 110002 C London 47 110002 C East 48 110003 RM West 45 110003 RM

A quick question that I've had only partial success in answering. I have a multivariate dataset, and would like to extract some simple univariate information from it grouped by treatments, etc. I am encountering two problems however Note: I am importing my data with my_data <- read.csv("/path/data.csv") 1) Scoping of unstack If I attempt sorted_data <- unstack(response,

...that I would appreciate an easy solution if there is any. The current data structure (variable names): ID, TIME, BUY-A, BUY-B, SELL-A, SELL-B Achieved structure (with the reshape command or the reshape package) ID, TIME, BUY-A ID, TIME, BUY-B ID, TIME, SELL-A ID, TIME, SELL-B This is regular unstacking with two identifier variables. Nothing special though. What I am looking for and did not manage is the following structure: ID, TIME, BUY-A, SELL-A ID, TIME, BUY-B, SELL-B I am quite sure it's pretty easy, but I could not find how to do this. Thanks a bunch, Daniel

Hello all,, Im looking for a simple function to produce a crosstab from a dumped sql query result. Its very hard to produce crosstabs with most databases (Access being the exception), so with the vast array of R packages, Im sure this has to have already been implemented somewhere. Examples are always good: Take a csv dump like name code user1 100 user2 100 user1 200 user2 210 user1 300 user2

stack() seems to drop empty levels. Perhaps there could be a drop=FALSE argument if one wanted all the original levels. In the example below, we may wish to retain level "b" in s$ind even though component LL$b has length 0. > LL <- list(a = 1:3, b = list()) > s <- stack(LL) > str(s) 'data.frame': 3 obs. of 2 variables: $ values: int 1 2 3 $ ind : Factor

Hello All, I was wondering if it's possible to reshape data from long to wide in R without using a "timevar". I've pasted some sample data below along with some code. The data are sorted by Subject and Drug. I want to transpose the Drug variable into multiple columns in alphabetical order. My data have a variable called "RowNo" that functions almost like a

Hi all, Thanks a lot for anyone's help in advance. I am trying to find a way to compute the day-to-day return (log return) from a n x r matrix containing, n different stocks and price quotes over r days. The time series of prices are already split by using unstack function. For the result, I would like to see a n x (r-1) matrix, where by each entry is the day-over-day return of

Hello All: I am very new to R and am trying to import some (107) text files into R while simultaneously manipulating the data into a structure that I can use. Below is a description of what I am trying to ultimately accomplish. However, I find that I am unable to even read one file into R using the read.table function. I get the following error: > test<-read.table("test4.txt")

Hello R - users, This may sound simple to may people: I have a list of data as follows type value y 7 y 7 y 8 y 8 y 8 y 9 y 9 y 9 y 9 y 10 y 10 y 10 y 10 y 11 y 11 y 12 y 12 y 14 y 14 y 14 y 15 y 17 y 20 y 20 y 20 y 20 y 25

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Dear R-helpers, my data.frame is of the form x <- data.frame( f=gl(4,3), X=rep(0:2,4), p=c(.1,.2,.3)) x f X p 1 1 0 0.1 2 1 1 0.2 3 1 2 0.3 4 2 0 0.1 5 2 1 0.2 6 2 2 0.3 7 3 0 0.1 8 3 1 0.2 9 3 2 0.3 10 4 0 0.1 11 4 1 0.2 12 4 2 0.3 which tabulates some values p(X) for several factors f. Now I want to put it in "wide"

Folks, This is probably a "help me google this properly, please"-type of question. In TIBCO Spotfire, there is a procedure called "line similarity". I use this to determine which observations show a growing, stable or declining pattern... sort of like a mini-regression on the time-line for each observation. So of the input is

------- Forwarded message follows ------- From: Petr Pikal <petr.pikal at precheza.cz> To: Henrik Parn <henrik.parn at bio.ntnu.no> Subject: Re: [R] paired t-test. Need to rearrange data? Date sent: Tue, 08 Aug 2006 16:13:47 +0200 Hi Uff, it takes me a bit headache but this shall do it ?unstack ?table ?t new.list<-unstack(test.data,y~id)

Hi, I'm trying to analyse some time series data on dissolved organic nitrogen. Because it has gaps in it, I try to interpolate (linear) with the regul method from the pastecs package. I have a number of stations with measurement series in a matrix constructed from a data frame with the unstack method (temp) I also used the unstack method to make a similar matrix for the time points

The Examples section of 'unstack' includes: formula(PlantGrowth) # check the default formula I wanted to add a formula to my own data.frame (for unstacking), so I start looking: ?formula # Nothing here about adding a formula to data attr(PlantGrowth, "formula") # Nothing here--c.f. groupedData objects dput(PlantGrowth) # Hmm, no formula here either ?formula.data.frame # Aliased to formula. Growing more frustrated. After more experimentati...

Dear All, I have a large data frame ( 2700000 lines and 14 columns), and I would like to extract the information in a particular way illustrated below: Given a data frame "df": > col1=sample(c(0,1),10, rep=T) > names = factor(c(rep("A",5),rep("B",5))) > df = data.frame(names,col1) > df names col1 1 A 1 2 A 0 3 A 1 4 A