similar to: Read in dataset without saving it

Hi, I am confused by results from: > ddply(aa, names(aa), colwise(sum)) I thought ddply was just calling colwise(sum)() with each column. However ddply() returns a 13 x 5 result !! The general result I expected is similar to that of apply() , or using colwise(sum)() alone. Shouldn't ddply() produce the same ? Thanks in advance for your help, - Stuart Andrews >

My data frame consists of character variables, factors, and proportions, something like c1 <- c("A", "B", "C", "C") c2 <- factor(c(1, 1, 2, 2), labels = c("Y","N")) x <- c(0.5234, 0.6919, 0.2307, 0.1160) y <- c(0.9251, 0.7616, 0.3624, 0.4462) df <- data.frame(c1, c2, x, y) pct <- function(x) round(100*x, 1) I want to

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

Hi, I have encountered this error when attempting a One-way Repeated-measure ANOVA with my data. I have read the "Anova in car: SSPE apparently deficient rank" thread by I'm not sure the within-subject interaction has more degrees of freedom than subjects in my case. I have prepared the following testing script: rm(list = ls())

plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to: * fit the same model to subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise transformations like scaling or standardising *

plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to: * fit the same model to subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise transformations like scaling or standardising *

I want to apply a more complicated function than what I use in my example, but the idea is the same: Suppose you have a data frame named x and you want to a function applied to each variable, we'll just use the quantile function for this example. I'm trying all sorts of apply functions, but not having luck. My best guess would be: sapply(x, FUN=quantile) -- View this message in

Dear R users, I have a dataframe which consists of variables of type numeric and factor. What is the easiest way to split up the dataframe to two dataframe which contain all variables of the type numeric resp. factors? Thank you very much for your efforts in advance! Best, Martin

Hi All, Year Area Q Bin FD I have a large dataset I need to re-structure. It looks something like this: 2000 1 1 5 0 2000 1 1 10 1 2000 1 1 15 23 2000 1 1 20 12 2000 1 1 25 1 2000 2 1 5 1 2000 2 1 10 3 2000 2 1 15 15 2000 2 1 20 11 2000 2 1 25 3 2000 1 2 5 0 2000 1 2 10 1 2000 1 2 15 23 2000 1 2 20 12 2000 1 2 25 1 2000 2 2 5 1 2000 2 2 10 3 2000 2 2 15 15 2000 2 2 20 11

# plyr plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to: * fit the same model each patient subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise

# plyr plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to: * fit the same model each patient subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise

Dear all R2.10 WinXP I have a dataset dealing with the way different wheat cultivars build their yield. Wheat ears are organised in spikelets where the spikelets can be numbered from the bottom, with even numbers on one side and odd on the other. I know how many kernels there were in each spikelet after some months spent counting them... Now I want to illustrate the differences between the

I'm trying to draw an arrow with a curved shaft on the graph as a straight one looks messy on a detailed graph. I've looked in arrows but it doesn't seem to give an option. larrows doesn't look much more promising. I had a look in the archive and couldn't find anything. Any thoughts? Thanks Paul -- View this message in context:

This was my initial attempt at creating a title on a graph of the R squared value: x<-rnorm(10) y<-rnorm(10) plot(x,y, main=paste(expression(R^2)," = ",round(summary(lm(y~ x))$r.squared, digits=3), sep="")) I've read various other posts that say expression needs to be taken outside the paste, but I can't seem to get it work as the following fails plot(x,y,

Dear R-help, First I apologize if my question is quite simple. I need add some of data in the first place my dataset, how can I do that. I have tried with rbind, but I did not succes. 0.1 3.6 0.4 0.9 rose 4.1 4.0 1.2 1.2 rose 4.4 3.2 1.9 0.5 rose 4.6 1.1 1.1 0.2 rose For example,

Hi, You may need ?split(), or ?aggregate() or ?ddply() from library(plyr) dat1 <- read.table(tex="1 2 4 7 8 9 1 4 5 8 9 1 4 5 6 9 2 3 4 8 3 6 7 8 1 5 6 9 2 5 7 9",header=FALSE,sep="",fill=TRUE)? ## ?res1 <- do.call(rbind,lapply(split(dat1,dat1[,1]),function(x) c(V1=x[1,1],colSums(x[,-1],na.rm=TRUE))))

Dear all, Without a loop, I would like transform 3 numeric vectors empty of 0/1 of same length Vec1 : transform 1 to A and 0 to "" Vec2 : transform 1 to B and 0 to "" Vec3 : transform 1 to C and 0 to "" to obtain only 1 vector Vec who is the paste of the 3 vectors (Ex : ABC, BC, AC, AB,...) Any idea ? Thank you for your help -- Michel ARNAUD

> An orphaned package? anyone in Switzerland know if there's an alternative? Note the email. I guess CRAN-R should be notified. regards, Bob C > The original message was received at Fri, 6 Apr 2007 16:32:57 -0700 > from vayu.arc.nasa.gov [143.232.122.22] > > ----- The following addresses had permanent fatal errors ----- > <juerg.schmidli at env.ethz.ch> >

I'm trying to assign NAs to values that satisfy certain conditions (more complex than shown below) and it gives the right result, but breaks the loop having done the first one viz: new<-c(rep(5,4),6) for (i in 1:6) {new[new[i]>5.5][i]<-NA} gives the correct result, though an error message appears which causes a break if it's in a loop. If I can get rid of the error message and

Hello R-helpers: I have data like this: sample replicate height weight age A 1.00 12.0 0.64 6.00 A 2.00 12.2 0.38 6.00 A 3.00 12.4 0.49 6.00 B 1.00 12.7 0.65 4.00 B 2.00 12.8 0.78 5.00 C 1.00 11.9 0.45 6.00 C 2.00 11.84 0.44 2.00 C 3.00 11.43 0.32 3.00 C 4.00 10.24 0.84 4.00 D