search for: summarybi

Hello Everyone- I'm calculating summary statistics on a dataset (~4000 records, observations are not uniformly distributed) using summaryBy and trying to add a column with the number of observations to the output as well. What occurs to me is to use nrow(), but this doesn't appear to be working I'm able to replicate the same results with an example from the summaryBy docs:

Dear Soren and R users: I am trying to use the summaryBy function with weights. Is this possible? An example that illustrates what I am trying to do follows: library(doBy) ## make up some data response = rnorm(100) group = c(rep(1,20), rep(2,20), rep(3,20), rep(4,20), rep(5,20)) weights = runif(100, 0, 1) mydata = data.frame(response,group,weights) ## run summaryBy without weights:

Hi Folks, I'm trying to cut my data inside the summaryBy function. Perhaps formulas don't work that way? I'd like to avoid adding another column if possible, but if I have to, I have to. Any ideas? Thanks, Allie require(doBy) df = dataframe(a <- rnorm(100), b <-rnorm(100)) summaryBy(a ~ cut(b,c(-100,-1,1,100)), data=df) # preferred solution, but it throws an

Dear users, I'm trying to learn how to use the "...". I have written a function (simplified here) that uses doBy::summaryBy(): # 'dat' is a data.frame from which the aggregation is computed # 'vec_cat' is a integer vector defining which columns of the data.frame should be use on the right side of the formula # 'stat_fun' is the function that will be run to

Hi, since I have quite large tables and the processing takes quite a while I am curious if I can improve the performance of this aggregation somehow: At the moment I am using summaryBy from the doBy package under R 2.4.0, Win2K. summaryBy(soc_s6aq5 + soc_s6aq7 + soc_s6aq9 + soc_s6aq11 ~ hh + comgroup,soc6a,postfix=c("","","",""),FUN=sum, na.rm=T) The

The R script below gives values of 1 for all minimum values when I use a custom function in summaryBy. I get the correct values when I use FUN=min directly. Any help is much appreciated. The continuous information provided in this forum is fabulous as are the different R packages available. Rene # Simulated simplified data Subj <- rep(1:4, each=6) Analyte <-

Hi, first I want to thank all of you for the quick aid which is provided here on the list during all times. Thanks a lot for that! Then, I have a problem using summaryBy which most probably is a problem of wrong use by me or the like: I use this command: summaryBy(total+total.inf~gr, aE, FUN=sum) where aE is a > str(aE) 'data.frame': 127880 obs. of 16 variables: $ gr

I'm trying to use a self-written function with the summaryBy function (doBy package). I have lots of data from Monte Carlo experiments comparing different estimators across different (combinations of) parameter values, similar to the following form: colnames(mydata) <- c("X", "b0", "b1", # parameter combination, corresponding (true) parameter values

Full_Name: Marc Paterno Version: 2.9.2 OS: Mac OS X 10.5.8 Submission from: (NULL) (99.53.212.55) summaryBy() produces incorrect results when given some data frames. Below is a transcript of a session showing the result, in a data frame with 2 observations of 2 variables. ------------------- thomas:999 paterno$ R --vanilla R version 2.9.2 (2009-08-24) Copyright (C) 2009 The R Foundation for

I am a very novice R user, a social scientist (linguist) who is trying to learn to use R after being very familiar with SPSS. Please be kind! My concern: I cannot figure out a way to get an accurate count of observations of one column of data split by a factor when there are NAs in the data. I know how to use commands like tapply and summaryBy to obtain other summary statistics I am interested

I need to compute the mean and the standard deviation of a data set and would like to have the results in one table/data frame. I call tapply() two times and do then merge the resulting tables to have them all in one table. Is there any way to tell tapply() to use the functions mean and sd within one function call? Something like tapply(data$response, list(data$targets, data$conditions), c(mean,

Wouldn't something like table(status) give you want you want? E.g.: R> status <- factor(c("A", "B", "A", NA, "A", "B")) R> table(status) status A B 3 2 Andy From: Jenifer Larson-Hall > > I am a very novice R user, a social scientist (linguist) who > is trying to learn to use R after being very familiar with >

hi all - i'm just wondering what sort of code people write to essentially performa an aggregate call, but with different functions being applied to the various columns. for example, if i have a data frame x and would like to marginalize by a factor f for the rows, but apply mean() to col1 and median() to col2. if i wanted to apply mean() to both columns, i would call: aggregate(x, list(f),

Hi, I was wondering if there is an easy way to accomplish the following in R: Often I want to apply a function, e.g. weighted.quantile from the Hmisc package to grouped subsets of a data.frame (grouping variable) but then I also need to hand over the weights which seems not possible with summaryBy or aggregate or the like. Is there a function to do this? Currently I do this with loops but it

I large datset that includes subjects(ID), Dates and events that need to be counted.  Not every date includes an event, and I need to only count one event per 30days, per subject.  So in essence, I need to create a 30-day "black out" period during which time an event cannot be "counted" for each subject.  The reason is that a rule has been set up, whereby a subject can only be

Hi all, I'm working with a sizable dataset that I'd like to summarize, but I can't find a tool or function that will do quite what I'd like. Basically, I'd like to summarize the data by fully crossing three variables and getting a count of the number of observations for every level of that 3-way interaction. For example, if factors A, B, and C each have 3 levels (all of

Wow.. thanks for the deluge of responses! Aggregate seems like the way to go here. But, suppose that instead of integers in column V2, I actually have dates (and instead of keeping the minimum integer, I want to keep the earliest date): > df =

Hello, unfortunately, I don't know a better subject. I would like to be very flexible in how to process my data. Assume the following dataset: par1 <- seq(0,1,length.out = 100) par2 <- seq(1,100) fac1 <- factor(rep(c("group1", "group2"), each = 50)) fac2 <- factor(rep(c("group3", "group4", "group5", "group6"), each =

Hello, struggling with the very basic needs... :( any help appreciated. #using the package doBY #who drinks how much beer per day and therefor cannot calculate rowise maxvals evaluation=data.frame(date=c(1,2,3,4,5,6,7,8,9), name=c("Michael","Steve","Bob", "Michael","Steve","Bob","Michael","Steve","Bob"),

Hello I have a table of this kind: function x1 x2 x3 2.232 1 1 1.00 2.242 1 1 1.01 2.732 1 1 1.02 2.770 1 2 1.00 1.932 1 2 1.01 2.132 1 2 1.02 3.222 1.2 1 1 ..... ... .. .. The table represents the values of a function(x1, x2, x3) for each combination x1, x2, x3. I'd like to generate a plot where each point has the coordinates x=x1, y=x2,