similar to: Is it possible to only read a subset by read.table ?

Dear all, I read.table a 17MB tabulator separated table with 483 variables(mostly numeric) and 15000 observations into R. This takes a few seconds with R 2.3.1 on windows 2000, but it takes several minutes on my Linux machine. The linux machine is Ubuntu 6.06, 256 MR RAM, Athlon 1600 processor. The windows hardware is better (Pentium 4, 512 RAM), but it shouldn't make such a difference.

Hi all, I have data like this: >sample <- read.csv(file="sample.csv",sep=",",header=TRUE) > sample stdate Domain sex age Login 1 01/11/09 xxx FeMale 25 2 2 01/11/09 xxx FeMale 35 4 3 01/11/09 xxx Male 18 30 4 01/11/09 xxx Male 31 3 5 02/11/09 xxx Male 32 11 6 02/11/09 xxx Male 31 1 7 02/11/09

Dear R-helpers & bioconductor Sorry for cross-posting, this concerns R-programming stuff applied on Bioconductor context. Also sorry for this long message, I try to be complete in my request. I am trying to write a subset method for a specific class (ExpressionSet from Bioconductor) allowing selection more flexible than "[" method . The schema I am thinking for is the following:

Hello helpers, This is probably quite simple, but I'm stuck. I want to create a summary statistics table with frequencies and summary statistics for a large number of variables. The problem here is that (1) there are two different classes of categories (sex, type of substance abuse and type of treatent) which overlap, (2) the data for different variables should be presented in different

Suppose my data looks like this: Obs, Male, Female, Height 1, T, F, 66 2, F, T, 64 3, T, F, 59 4, T, F, 55 5, F, T, 62 6, T, F, 67 7, T, F, 58 8,

I'm not sure how to best explain what I am after but here goes. I have a data frame with 2 geographical factors. One is the major region the other is the component regions. I am trying to process all the regions at the same time without using "for". So I need (think, I do) a list of matrices each structured according to the number of subregions within each region. So is there a

The data is in the attachment. What I wanna get is: , , Sex = Male Eye Hair Brown Blue Hazel Green Black 32 11 10 3 Brown 53 50 25 15 Red 10 10 7 7 Blond 3 30 5 8 , , Sex = Female Eye Hair Brown Blue Hazel Green Black 36 9 5 2 Brown 66 34 29 14 Red 16 7 7 7 Blond 4

Good day all, My statisticians want an R procedure that will produce grouped stacked barplots. Barplot will stack or group, but not both. The ftable function can produce a table of the exact form they want, but the barplot doesn't show all the divisions we want. For an example, here's the sample from the help file for "ftable:" data(Titanic) ftable(Titanic, row.vars = 1:3)

Hello, I'm trying to do bar plot where 'sex' will be the category axis and 'occupation' will represent the bars and the clusters will represent the mean 'income'. sex occupation income 1 female j 12 2 male b 34 3 male j 22 4 female j 54 5 male b 33 6

Hello R-users/experts, I am new to R- I have a simple question: Let say I have a data set as follows temp:[file attached] the data structure is a follows: sex age female 28 female 53 female 53 female 36 male 42 male 29 male 43 male 36 male 41 Here we are grouping all male value into male and all female value in to female

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

I would like to have a table with some constants to use them later on for a drop down menu. How can this be done? My table looks like Table with constants ------------------------ id | key | value | type ------------------------ 1 | M | Male | sex .... I know it can be done like this <% select ''object'', ''method'', Constants.find(:all, :select =>

Dear list, I have following data set, which I want to plot the "Scale" variable on the x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The Mean value of each Ageclass for each sex would be connected by a line. Totally, there should be 6 lines, from which three present the Mean values of each Ageclass for respective sex. Are there any easy ways to do

I'm puzzled by the following problem, which appears when attempting to run an analysis on part of a dataset: If I try: csubset <- dat$Diagnosis==0 cont <- lme(fixed=cform, random = ~1|StudyName, data=dat,subset=csubset,na.action=na.omit) Then I get: Error in eval(expr, envir, enclos) : Object "csubset" not found But if I do

dear£º in the example£¨nomogram£©£¬I don't understand the meanings of the program which have been marked by red line.And how to compile the program(L <- .4*(sex=='male') + .045*(age-50) + (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))). n <- 1000 # define sample size set.seed(17) # so can reproduce the results age <- rnorm(n, 50, 10)

I currently have a data set in which gender is inputed as "Male" and "Female" , and I'm trying to convert this into "1" and "0". I found a website which reccomended using two commands: data$scode[data$sex=="M"] <- "1" data$scode[data$sex=="F"] <- "2" to convert to numbers, and: data$scode <-

Hi, I don't know how to make prediction with a factor in the linear model. Say yd=c(1,2,3,4,5) > sl=c(2,3,4,5,6) > sex=c("male","male","female","female","male") > sex=factor(sex) > m=lm(sl~yd+sex+sex:yd) How to make a prediction with new data like yd=c(4,5,6,7,8) for male and female separately ? Thank you very

Hi, To be able to match cases with a benchmark I need to have a data.frame with a character id variable. however, I am surprised why this seems to be so hard. In fact I was unable to succeed. Here is what I tried: >test1 <-expand.grid(ID = 1:2, sex = c("male","female")) >is(test1[,2]) [1] "factor" "oldClass" >test2 <-expand.grid(ID =

Hi dear listers Do you know how to made a mean by one or more categorical variables? I can do that quite easy on SAS by in R I just can't do it E.g. Some fishes Sex Lenght male 15 fema 20 fema 17 fema 19 male 18 So the idea is mean(Lenght) by sex, in order to have sex: Male mean=XX Sex: Fema mean=YY In this case is quite easy to do it by a loop, but I have a huge DB so is not an

Dear people, I have got a question concerning the underlying numerical codes when reading an SPSS file into R. I used the package foreign and when I look at a variable I get the verbal codes. I would like to know how it is possible to get the underlying numerical codes as output, which are the same as in my SPSS file. Thank you very much in advance for your help! Marion [[alternative HTML