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:

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

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

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?

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

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,

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

I have been using ddply to do aggregation, and I frequently define a single aggregation function that I use to aggregate over different groups. For example, require(plyr) dat <- data.frame(x = sample(3, 100, replace=TRUE), y = sample(3, 100, replace = TRUE), z = rnorm(100)) f <- function(x) { data.frame(mean.z = mean(x$z), sd.z = sd(x$z)) } ddply(dat, "x", f) ddply(dat,

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)

I'm wondering if anyone can give some basic advice about how to approach a specific task in R. I'm new to R but have used SAS for many years, and while I can muscle through a lot of the code details, I'm unsure of a few things. Specific questions: If I have to perform a set of actions on a group of files, should I use a loop (I feel like I've heard people say to avoid looping

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

I have a table that looks like this: measurement?? ?date??? door ?? color 0.93529385?? ?513?? ?open?? ?red 0.97419293?? ?420??? open ?? red 0.962053514?? ?513?? ?closed?? ?red 0.963909937?? ?1230?? ?open?? ?blue 0.97652034?? ?1230?? ?open?? ?green 0.989310795?? ?1230?? ?closed?? ?blue 0.9941022?? ?917?? ?closed?? ?yellow I would like to create a table that has: Open measurement, Closed

Hi, I would like to extract the last row of each group in a data frame. The data frame is as follows Name Value A 1 A 2 A 3 B 4 B 8 C 2 D 3 I would like to get a data frame as Name Value A 3 B 8 C 2 D 3 Thank you for your suggestions in advance Jeff

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?

Dear R-users, I have a dataset as like below, and I want to subtotal the values of rice,wheat and maize by year for each fid. fid      year     rice     wheat      maize ------------------------------------------------ 1        1995      5        NA           NA 1        1995      NA        3           NA 1        1995      NA       NA           2 1        1996      4        NA           NA 1  

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