similar to: "sequeeze" a data frame

Another request for help implementing the 'apply' functions to avoid a loop structure... I am working with a data set that includes lab measurements taken at different dates for the subjects, with some subjects having more results than others. I would like to average lab results for each subject that were taken on the same day. I can do this using a for loop, but would like to know how

I have a data frame containing children, with variables 'year' = birth year, and 'm.id' = mother's id number. Let's assume that all the births of each mother is represented in the data frame. Now I want to create a subset of this data frame containing all children, whose mother's first birth was in the year 1816 or later. This seems to work: mid <-

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I

I am working with a longitudinal data set in the long format. This data set has three observations per grade level per year. Here are the first 10 rows of the data frame: >tenn.dat[1:10,] year schid type grade gain se new cohort 6 2001 100005 5 4 33.1 3.5 4 3 7 2002 100005 5 4 33.9 3.9 4 2 8 2003 100005 5 4 32.3 4.2 4 1 10 2001 100005

Dear Colleagues, Apologies for a long email to ask what I feel may be a very simple question; I figure it's better to overspecify my situation. I was asked a question, recently, by a colleague in my department about pre-aggregating variables, i.e., computing the mean of defined subsets of a data frame. Naturally, I thought of the 'by' and 'tapply' functions, as

I read answers to questions including the words "tapply" and "weighted.mean", but I didn't understand either the problem (data) or the solution provided. Here is my question ... > dat[1:10,] GROUP VALUE FREQUENCY 1 2 2 78 2 2 3 40 3 2 4 16 4 2 5 3 5 2 6 1 6 2 8 1 7

Hi, there I'm trying to plot what is returned from a call to tapply, and can't figure out how to do it. My guess is that it has something to do with the inclusion of row names when you ask for the values you're interested in, but if anyone has any ideas on how to get it to work, that would be stellar. Here's some example code: y1<-rnorm(40, 2) x1<-rep(1:2, each=20)

Dear all, I want to calculate mean values for multiple rows: structure(list(Name = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("AKT", "CKT"), class = "factor"), val1 = c(2, 3, 2, 2, 2, 5, 3, 8, 2), val2. = c(4, 5, 4, 8, 4, 8, 4, 7, 4), val3 = c(5, 6, 5, 9, 5, 9, 5, 9, 5)), .Names = c("Name", "val1", "val2.",

I read in a thread in r-help today that the windows device in 2.6 supports transparency, so I tried an example and had some issues. The density plots should be filled with transparent color in the following example (similar to the points), however the color is "fully" transparent. This works in the Cairo device, but not in the windows device. Thanks, --Matt Matt Austin

Hi, I'm a database admin for a database which manage chromatographic results of products during stability studies. I use R for the reporting of the results in MS Word through R2wd. But now I think I need your help: suppose we have the following data frame: ID rrt Mnd Result 1 0.45 0 0.10 1 0.48 0 0.30 1 1.24 0 0.50 2 0.45 3 0.20 2 0.48 3 0.60 2 1.22 3 0.40 3

Hi, I am relatively new to R; when creating functions, I run into problems with missing values. I would like my functions to ignore rows with missing values for arguments of my function) in the analysis (as for example is the case in STATA). Note that I don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my

Hi, I'd like to ask you a question again. It is basically about data frames, NAs and tabulate function. I have this data frame. I already used this in one of the previous questions of mine. It intentionally looks this simple, my real 'df' dataframe is much bigger actually and again, I am not willing to annoy anyone with huge databases... So, my database: id

Dear helpers, I've come up with what is probably a simple problem, but I cannot find the solution. I have a data-set containing survey-data from several countries. What I want to do is to perform some regression analyses, for each country separately. The question is, how to do this nicely (thus without repeating the same syntax with another `subset' argument). I thought of the

Dear R-users, I am working with R version 2.10.1. Say I have is a simple function like this: > my.fun <- function(x, mult) mult*sum(x) Now, I want to apply this function along with some other (say 'max') to a simple data.frame, like: > dat <- data.frame(x = 1:4, grp = c("a","a","b","b")) Ideally, the result would look something like

Hi all (really probably just Deepayan): In the plot below I want to add text on either side of each violin plot that indicates the number of observations that are either positive or negative. I'm trying to do this with ltext() and I've also monkeyed about with panel.text(). The code below is generally what I want but my calls to ltext() are wrong and I'm not sure how to fix them.

Dear R users, I am encoutering the following problem: I have a dataset with a 'unique_id' and different 'visit_date' (formatted as.Date, "%d/%m/%Y") per unique_id. I would like to create a new variable with the most recent date of visit per unique_id as shown below. unique_id visit_date last_visit_date 1 01/06/2010 01/06/2011 1 01/01/2011 01/06/2011 1

I think I understand tapply but i still can't figure out how to do the following. I have a dataframe where some of the column names are the same and i want to make a new dataframe where columns that have the same name are averaged by row. so, if the data frame, DF, was AAA BBB CCC AAA DDD 1 0 7 11 13 2 0 8 12 14 3 0 6 0 15

Suppose I have a data frame with two columns ``district'' and ``score'' --- score is numeric; district may be considered categorical. I wish to append to this data frame a third column whose entries are the ranks of ``score'' ***within*** district. I've tried fiddling about with tapply() and by() but the result is a list whose i-th component consists of the ranks of

Consider the following situation: we have quantified algal concentrations for a variety of species using many samples at each of three years. It seems to make sense to generate a line plot (matplot-like), with each species plotted as a separate line, with the points connected to emphasize the temporal pattern. The problem: lots of overlapping error bars. The question: from both a

Hello World, I have a function that makes pairwise comparisons between two strings. I would like to apply this function to my data (which consists of columns with different strings) in the way that it compares the first with the second entry, and then the third with the fourth, and then the fifth with the sixth, and so on down each column... So (2x-1) and (2x) would be the different entries to be