similar to: selecting first row of a variable with long-format data

Hi All, I am interested in aggregating a data frame based on 2 categories--mean effect size (r) for each 'id's' 'mod1'. The 'with' function works well when aggregating on one category (e.g., based on 'id' below) but doesnt work if I try 2 categories. How can this be accomplished? # sample data id<-c(1,1,1,rep(4:12)) n<-c(10,20,13,22,28,12,12,36,19,12,

Hi All, I'm conducting a meta-analysis and have taken a data.frame with multiple rows per study (for each effect size) and performed a weighted average of effect size for each study. This results in a reduced # of rows. I am particularly interested in simply reducing the additional variables in the data.frame to the first row of the corresponding id variable. For example:

Dear R, I've got a data frame with children examined multiple times and at various ages. I'm trying to find the first age at which another variable (LDL-Cholesterol) is >= 130 mg/dL; for some children, this may never happen. I can do this with transformBy and ddply, but with 10,000 different children, these functions take some time on my PCs - is there a faster way to do this in R?

Hi, I have this sample data below and would like to create a list of matricies. setseed(1254) id <- c(1,1,1,1 ,2,2,2) o <- as.factor(c(1:4, 1, 3, 4)) r <- rep(.5, 7) v <- rnorm(7) s <- rnorm(7) dat <-data.frame(id, o, r, v, s) dat #> dat # id o r v s # 1 1 0.5 0.7024631 2.0813672 # 1 2 0.5 -0.5541955 0.1095156 # 1 3 0.5 -1.0418167 0.4164930 # 1

I have the following data ID x y time 1 10 20 0 1 10 30 1 1 10 40 2 2 12 23 0 2 12 25 1 2 12 28 2 2 12 38 3 3 5 10 0 3 5 15 2 ..... x is time invariant, ID is the subject id number, y is changing over time. I want to find out the difference between the first and last observed y value for each subject and get a table like ID x y 1 10 20 2 12 15 3 5 5 ...... Is there any easy way to generate

Hi, Is there an easy way to remove dataframe rows without duplicated values of a specified column ('id')? e.g., dat <- data.frame(id = c(1,1,1,2,3,3), value = c(5,6,7,4,5,4), value2 = c(1,4,3,3,4,3)) dat id value value2 1 1 5 1 2 1 6 4 3 1 7 3 4 2 4 3 5 3 5 4 6 3 4 3 This is sample data and the real data has hundreds of

Hi, I want to sort a data frame by multiple columns and then take the first record in each unique level of the "by" group I used to sort the data frame. Does someone have an example of how to do this? Thanks, Matt -- It is from the wellspring of our despair and the places that we are broken that we come to repair the world. -- Murray Waas

Hi All, Im interested in creating a function that will convert a variable within a data.frame to a factor while retaining the original name (yes, I know that I can just: var <-factor(var) but I need it as a function for other purposes). e.g.: # this was an attempt but fails. facts <- function(meta, mod, modname = "spec") { meta$mod <- factor(meta$mod)

Hello, Having the matrix d > d value value2 class 1 1 1 x 2 2 2 x 3 3 3 x 4 4 2 x 5 5 1 y 6 11 3 y 7 12 4 z 8 13 5 z 9 14 6 z 10 15 7 z I want to calculate the means and cov matrix for groups x,y,z. I know how to do it the long way. I tried to use tapply and

Hi, I have a data set that I'd like to run logistic regressions on, using ddply to speed up the computation of many models with different combinations of variables. I would like to run regressions on every unique two-variable combination in a portion of my data set, but I can't quite figure out how to do using ddply. The data set looks like this, with "status" as

Hello everyone, I was asked to repost this again, sorry for any inconvenience. I'm looking replacement for ddply function from plyr package. Function allows to apply function by category stored in any column/columns. Regular loops or lapplys slow down greatly because my unique combination count exceeds 9000. Is there any available solution which allow me to apply function by category?

I have a data frame called "pose": DESCRIPTION QUANITY CLOSING.PRICE 1 WHEAT May/10 1 467.75 2 WHEAT May/10 2 467.75 3 WHEAT May/10 1 467.75 4 WHEAT May/10 1 467.75 5 COTTON NO.2 May/10 1 78.13 6 COTTON NO.2 May/10 3 78.13 7 COTTON NO.2 May/10 1 78.13

Dear R-users, I am trying to get the plyr syntax right, without much success. Given: d<- data.frame(cbind(x=1,y=seq(20100801,20100830,1))) names(d)<-c("first", "daterep") d2<-d # I can convert the daterep column in place the classic way: d$daterep<-as.Date(strptime(d$daterep, format="%Y%m%d")) # How to do it the plyr way? ddply(d2,

Dear list, I'll try to be more clear in explaining my problem. I have a data frame like this called X: CLUSTER YEAR variable value1 value2 M1 2005 EC01 NA NA M1 2006 EC01 2 5 M1 2007

Hello everyone, I have got the same problem, with the same error message. Using R 2.14.1, plyr 1.7.1, R.Studio 0.94.110, Windows XP The plyr mailing list does not provide any help until now. >require(plyr) >c(sample(c(1:100), 50, replace=TRUE))->V1 >c(rep( 1:5, 10))->f1 #variable to group V1 >data.frame(cbind(V1, f1))->DF >str(DF) >ddply(DF$V1, DF$f1,

Hello, I am looking for a way to subset a data frame by choosing the top ten maximum values from that dataframe. As well this occurs within some factor levels. ## I've used plyr here but I'm not married to this approach require(plyr) ## I've created a data.frame with two groups and then a id variable (y) df <- data.frame(x=rnorm(400, mean=20), y=1:400,

Dear all, I'm puzzled by the following example inspired by a recent question on R-help, cc <- textConnection("user_id website time 20 google 0930 21 yahoo 0935 20 facebook 1000 25 facebook 1015 61 google 0940") d <- read.table(cc, head=T) ; close(cc) table(d$user_id) # count the

I have a dataframe df with two columns x and y. I want to count the number of times a unique x, y combination occurs. For example x<- c(1,2,3,4,5,1,2,3,4) y<- c(1,2,3,4,5,1,2,4,1) df<-as.data.frame(cbind(x, y)) #what is the correct way to use ddply for this example? ddply(df, c('x','y', summarize, ??) #desired output -- format and order doesn't matter # (x, y)

Hello R help, I have a question similar to what is posted by someone before. my problem is that Instead of last assessment, I want to choose last two. I have a data set with several time assessments for each participant. I want to select the last assessment for each participant. My dataset looks like this: ID week outcome 1 2 14 1 4 28 1 6 42 4 2 14 4 6 46 4 9 64 4 9

Dear all, I'm stuck with a problem using plyr to process a rather large junk of data. What I'm trying to do is applying a moving average to all the subparts of the dataframe (the example data can be found here https://dl.dropboxusercontent.com/u/2414056/testData.Rdata). require(plyr) load("testData.Rdata") applyfilter<-function(x){ return(filter(x,rep(1/5, times=5))) }