similar to: multivariate graphs, averaging on some vars

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:

Hello, I have a set of data including age, wage and education level each called age76, wage76 and grade76 I want to know how i can calculate the average wage of people age 15 to 65 (each year separetly) , only for those who have an education level of 10 12 and 16... -- View this message in context: http://r.789695.n4.nabble.com/Conditional-average-tp4585313p4585313.html Sent from the R help

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

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, 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

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,

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 <-

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

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

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

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),

Hello: I hope none of you will mind helping a newbie. I'm a student research assistant working with a large data set in which observations are categorized according to two factors. I'm trying to calculate the group mean and variance of a variable (called 'hsgpa' in the example data presented below) to each observation , excluding that observation. For example, if there are

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 =

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

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Hi, my problem is as follows: I have a matrix of two rows like this: 2 2 3 4 4 4 5 5 6 1 1 2 1 3 3 2 1 1 Can I apply something like "group by" in sql? What I want to achieve is the some of second row for each unique entry of first row: 2 -> 2 (=1+1) 3 -> 2 4 -> 7 (=1+3+3) 5 -> 3 (=2+1) 6 -> 1 Thanks!! Henning

Hi all, I have a question about transforming the data from summary function. Let's say I have a data frame like this: > x = data.frame(a = c(rep("lev1", 5), rep("lev2", 5)), b = c(rnorm(5)+2, rnorm(5))) > x a b 1 lev1 1.5964765 2 lev1 2.2945609 3 lev1 3.5285787 4 lev1 1.4439838 5 lev1 2.2948826 6 lev2 1.7063506 7 lev2 -0.4042742 8 lev2

Hi, I have a data frame and want to merge adjacent rows if some condition is met. There's an obvious solution using a loop but it is prohibitively slow because my data frame is large. Is there an efficient canonical solution for that? > head(d) rt dur tid mood roi x 55 5523 200 4 subj 9 5 56 5523 52 4 subj 7 31 57 5523 209 4 subj 4 9 58 5523 188 4 subj 4 7