similar to: reshape

Hi, I'm trying to use reshape but I cannot quite understand how it works. Could somebody help me on this? Example, my data is something like: mydat <- data.frame(tree= 1:10, serra=rep(1:2, c(5,5)), bt01= 101:110, bt02= 201:210, bt03= 301:310, mm01= 9101:9110, mm02= 9201:9210, mm03= 9301:9310) > mydat tree serra bt01 bt02 bt03 mm01 mm02 mm03 1 1 1 101 201 301 9101 9201

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

I'd like to convert a data.frame from (long format): gen maxh resp 1 12.3 y . . . . . . where resp is a factor with levels "y" and "n" to the wide format: gen maxh.y maxh.n . . . . . . I've done it as follows: maxh.y <- split(maxh, resp)$y gy <- split(gen, resp)$y yes <-

Hello * I would like to reshape wide the following dataset: > rl <- read.dta("intermedi/rapporti_lavoro.dta") [c("id_rl","prog","sil_pi","sil_cf","sil_dat_avv")] > dim(rl) [1] 12964 5 > object.size(rl) 1194728 bytes > head(rl) id_rl prog sil_pi sil_cf sil_dat_avv 1 638 1 04567XXXXXX

I have two waves of a survey given to students at various middle schools and high schools, with student id numbers for each student. I am having difficulty reshaping the file from long to wide. My code is below: library(foreign) svy <- read.spss("studsur4.SAV") svy.wide <- reshape(svy, timevar="WAVE", idvar="id", direction="wide")

Hello, I have data frame like the one created below, ##input data Person <- c(1,1,1,1,1,1,2,2) Amount <- c(100,10,100,10,100,10,50,150) Date <- c("12/01/2012", "12/01/2012", "01/01/2013","01/01/2013","02/01/2013","02/01/2013","12/01/2012","12/01/2012") df <- data.frame(Person,Amount,Date) I would

I know there are a lot of reshape questions on the mailing list, but I haven't been able to find an answer to this particular issue. I am trying to get a datafame structured like this: > sub <- rep(1:5) > ta1 <- rep(1,5) > ta2 <- rep(2,5) > tb1<- rep(3,5) > tb2 <- rep(4,5) > DF <- data.frame(sub,ta1,ta2,tb1,tb2) > DF sub ta1 ta2 tb1 tb2 1

Full_Name: Kevin Wright Version: 1.4 OS: Windows 95 Submission from: (NULL) (170.54.59.160) Note: This was the 1.4 build for Windows that Brian Ripley made available. The first example in the help for reshape doesn't work for me. When I cut and paste, this is what happens: > data(Indometh,package="nls") > summary(Indometh) Subject time conc

Dear all, I'm interested in analysing a reapeated measure desing where plant height (H) was measured 3 times (Time). The experimental design include 2 fixed factor (say A and B) in which A is nested in B, and a random factor (C, the plot), using the aov(). So my first idea would be something like: aov(H ~ B * A %in% B * Time + Error(id) ) where id is the factor coded for the repeated

I don't quite understand the difference between the two methods for performing a chi-squared test on contingency tables: summary(table()) and chisq.test() They may different results. E.g.: aa <- gl(2, 10) bb <- as.factor(c(1,2,2,2,1,2,1,2,2,2,1,2,2,2,1,1,1,2,1,1)) aa <- c(aa, aa) bb <- c(bb, bb) table(aa, bb) summary(table(aa, bb)) chisq.test(aa, bb) Could somebody give me

Full_Name: Alexander L. Belikoff Version: 2.8.1 OS: Ubuntu 9.04 (x86_64) Submission from: (NULL) (67.244.71.200) I'm trying to reshape the following data frame: ID DATE1 DATE2 VALUE_TYPE VALUE 'abcd1233' 2009-11-12 2009-12-23 'TYPE1' 123.45 ... VALUE_TYPE is a string and is a factor with only 2 values

Hi all: I solved the previous stated problem in something of a brute force way (but it works). I seem to now be running into one little hiccup using reshape. Here is a quick snip of the data in long format: grade stability year schid 6 Grade 4 3 2001 100005 7 Grade 4 3 2002 100005 8 Grade 4 2 2003 100005 10 Grade 5 2 2001 100005 11 Grade 5

Dear R-collegues, I'm getting an error message (Error in round) when summarising a glm.nb model, and when using anova.negbin (in R 1.3.1 for windows): > m.nb <- glm.nb(tax ~ areal) > m.bn Call: glm.nb(formula = tax ~ areal, init.theta = 5.08829537115498, link = log) Coefficients: (Intercept) areal 3.03146 0.03182 Degrees of Freedom: 283 Total (i.e. Null); 282

I wonder if the 'sep' argument in reshape() is being ignored unintentionally: ## From example(reshape) df <- data.frame(id=rep(1:4,rep(2,4)), visit=I(rep(c("Before","After"),4)), x=rnorm(4), y=runif(4)) reshape(df, timevar="visit", idvar="id", direction="wide", sep = "_") id x.Before

When reshaping a dataframe in which there are unused factor levels in the id variable, I get the following error: Error in if (!all(really.constant)) warning(gettextf("some constant variables (%s) are really varying", : missing value where TRUE/FALSE needed For example, > df <- data.frame(i = factor(rep(1:5, each = 2)), t = factor(rep(1:2, 5)), x = rep(rbinom(5, 1,

Dear R-users, I'm sure it must be a specific function or a better way to convert matrix to x,y,z coordinates (and viceversa), than my function below (it works). Any help? m2coord <- function(m) { k <- nrow(m)*ncol(m) aa <- data.frame(r=1:k, c=1:k, v=1:k) k <- 0 for (i in 1:nrow(m)) for (j in 1:ncol(m)) { k <- k+1 aa$f[k]=i; aa$c[k]=j; aa$v[k]=m[i,j] } aa } Juli

Hi, I'm trying to reshape my data set from wide to tall format for multilevel modeling. Unfortunately, the function I typically use (make.univ from the multilevel package) does not appear to work with unbalanced data frames, which is what I'm dealing with. Below is an example of the columns of a data frame similar to what I'm working with: ID a1 a2 a4 b2 b3 b4 b5 b6 Below

I need to do a somewhat complex rearrangement of an existing dataframe that involves an "on-the-fly" conditional summary as well. I've tried to make the example as simple as possible. Code to produce the object being acted on is at the end of the message. I hope this isn't too much for a single posting. Any guidance will be much appreciated. The input example looks like

I have a dataset in "long" format that looks something like this: ID TEST RESULT 1 A 17 1 A 12 1 B 15 1 C 12 2 B 8 2 B 9 Now what I would like to do is transpose it like so: ID TEST A TEST B TEST C 1 17 15 12 1 12 . . 2

I have a dataframe that I'm trying to reshape, and need advice. My data: > klam.merge[200:225,] stream lulc x sumlength pct.lgth 200 1223030419685 92 0.25000000 9.89 2.52780586 201 1223030419686 23 0.00274154 4.73 0.05796068 202 1223030419686 41 0.75009917 4.73 15.85833341 203 1223030419686 42 2.65000000 4.73 56.02536998 204