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I'd like to summarize several variables in a data frame, for multiple groups, and store the results in a data.frame. To do so, I'm using by(). For example: df<-data.frame(a=1:10,b=11:20,c=21:30,grp1=c("x","y"),grp2=c("x","y"),grp3=c("x","y")) dfsum<-by(df[c("a","b","c")],

Hi, I wanted to generate a plot which is almost like the plot generated by the following codes. category <- paste("Geographical Category", 1:10) grp1 <- rnorm(10, mean=10, sd=10) grp2 <- rnorm(10, mean=20, sd=10) grp3 <- rnorm(10, mean=15, sd=10) grp4 <- rnorm(10, mean=12, sd=10) mydat <- data.frame(category,grp1,grp2,grp3,grp4) dat.m <- melt(mydat) p <-

Dear all Is there a clean plyr version of the following by() and do.call(rbind, ...) construct: > df<-data.frame(a=1:10,b=11:20,c=21:30,grp1=c("x","y"),grp2=c("x","y"),grp3=c("x","y")) > dfsum<-by(df[c("a","b","c")], df[c("grp1","grp2","grp3")], range) >

Dear friends, My R*C table is as follow: better good bad Goup1 16 71 37 Group2 0 4 61 Group3 1 6 57 Can I test if there are statistical significant between Group1 and Group2, Group2 and Group3, Group1 and Group2, taking into the multiple comparisons? The table can be set up using the following program: a<-matrix(data=c(16,71,37,0,4,61,1,6,57),nrow=3,byrow=TRUE) Thanks

I would like to divide a vector in 9 groups in a way that each number is present in only one group. In a vector of 783 I would like to divide in 9 different groups of 87 Example <- matrix(c(1:783),ncol = 1) s1 <- as.matrix(sample(Example,87, re = FALSE)) Example <- Example[-s1] s2 <- as.matrix(sample(Example,87, re = FALSE)) #however I don?t know how to remove the second group from

Hi friends, I have a matrix with following format. group var1 var2 .......varN c1 group1 1.2399 1.4990....-1.4829 c2 group4 0.8989 0.7849.....1.8933 ... ... c100 group10 ..... I want to draw a profile plot of each condition c1 to c100, which rows in above matrix and each line representing a row should be uniquely colored according to the group(1 to 10). I think this is simple task

Dear R-users, I state that this is for beginners, so you may ignore this in order not to be irritated. By the way, "patience" is another important thing, together with "kindness", we should keep in mind when we teach students and our own children as Jim Lemon pointed out well in the context of the Socratic method. You may know that being kind does not mean giving

Dear fellow R users, I would like to draw a "sunflowerplot" because I have data (decade by month) that plots multiple times on the same x-y co-ordinates. Further I would like to colour each of the points/sunflower leaves on the plot according to the group they belong to (i.e. which type of event each represents within that decade and month). I thought that this would be relatively

library(plyr) n<-100000 grp1<-sample(1:750, n, replace=T) grp2<-sample(1:750, n, replace=T) d<-data.frame(x=rnorm(n), y=rnorm(n), grp1=grp1, grp2=grp2) system.time({ d$avx1 <- ave(d$x, list(d$grp1, d$grp2)) d$avy1 <- ave(d$y, list(d$grp1, d$grp2)) }) # user system elapsed # 39.300 0.279 40.809 system.time({ d$avx2 <- ave(d$x, interaction(d$grp1, d$grp2, drop =

Hi, I have a data.frame that has a categorical variable, for which I would like to look at the distribution of levels of this variable, based on a grouping of two other variables. As an example: x <- data.frame(obs=sample(c('low', 'high'),100, replace=TRUE), grp1=sample(1:10, 100, replace=TRUE), grp2=runif(100)) cut.grp1 <- cut(x$grp1, 3) cut.grp2 <- cut(x$grp2, 3)

Hello Tyler, I want to bring to your attention the following document: "What happens if you omit the main effect in a regression model with an interaction?" (https://stats.idre.ucla.edu/stata/faq/what-happens-if-you-omit-the-main-effect-in-a-regression-model-with-an-interaction). This gives a useful review of the problem. Your example is Case 2: a continuous and a categorical regressor.

Hi folks, has anybody a simple solution for the following request? I have a group alias (all at company.com). (1) Only company.com accounts should be able to send an email to everybody in that company via all at company.com. (2) - rather optional: refine the restrictions, e.g. two groups, grp1 at company.com and grp2 at company.com. Grp1 members should be able to send mails to grp2 but not vice

Hello Tyler, Thank you for searching for, and finding, the basic description of the behavior of R in this matter. I think your example is in agreement with the book. But let me first note the following. You write: "F_j refers to a factor (variable) in a model and not a categorical factor". However: "a factor is a vector object used to specify a discrete classification"

Hi, I have a vector of data, that I group based on two factors via tapply. For each such grouping I would like to plot a pie chart. I can layout these pie charts in a matrix layout, correpsonding to the levels of the two factors. But I am getting stuck on how to label the rows and colums. My current approach looks like this: x <- data.frame(obs=sample(c('low', 'high'),100,

Hello all, I have arranged my data as per Dennis's suggestion in this post http://www.mail-archive.com/r-help at r-project.org/msg107156.html. the posted code works fine but when I try to apply it to my data, i get "> u2 <- ddply(xxm, .(plateid, cytokine), as.data.frame.function(f)) Error in t.test.formula(conc ~ Self_T1D, data = df, na.rm = T) : grouping factor must have

Hi experts I have a trouble in access rights I am running Samba 3.0.31 on Solaris 10 x86 64 bits as member server of an Active Directory 2003 R2 domain (MYDOMAIN) using Identity Management for Unix I set rights to access a sub folder of a Samba share. On Solaris the user "toto" jdoe can write a new file. From Windows, the same user can't. Itlooks like OK when the primary group

Hello Tyler, I rephrase my previous mail, as follows: In your example, T_i = X1:X2:X3. Let F_j = X3. (The numerical variables X1 and X2 are not encoded at all.) Then T_{i(j)} = X1:X2, which in the example is dropped from the model. Hence the X3 in T_i must be encoded by dummy variables, as indeed it is. Arie On Thu, Nov 2, 2017 at 4:11 PM, Tyler <tylermw at gmail.com> wrote: > Hi

Dear Helpful R Users, I am graphing some data using the beanplot, but I am having trouble getting the output I desire. I have five tanks (A-E) and 2 groups for each tank grp1 or grp2, except tank C where there is only grp1. (I only changed the grouprep to "C grp1" for the example) When I plot them, I would like A B C(only grp1 - half of the bean plot) then D and E (as full beans).

[R 2.0.0 on Linux] I tried: > df <- data.frame( grp1=factor( c('A' ,'A' ,'A' ,'D', 'D' ) ) , grp2=factor( c('a1','a2','a2','d1','d1') ) ) > df grp1 grp2 val 1 A a1 1 2 A a2 2 3 A a2 4 4 D d1 8 5 D d1 16 I got: > with( df, ave( val, grp1, grp2, FUN=sum ) )

Hello Tyler, You write that you understand what I am saying. However, I am now at loss about what exactly is the problem with the behavior of R. Here is a script which reproduces your experiments with three variables (excluding the full model): m=expand.grid(X1=c(1,-1),X2=c(1,-1),X3=c("A","B","C")) model.matrix(~(X1+X2+X3)^3-X1:X3,data=m)