similar to: Average Login based on date

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 All, I have the data some thing like this, I am showing here three days data only: > dummy.data <- read.table(file='dummy.txt',sep='', header=TRUE) > dummy.data StDate Domaindesc Logins 1 05/01/10 xxx 10 2 05/01/10 xxx 45 3 05/01/10 xxx 2 4 05/01/10 yyy 45 5 05/01/10 yyy 20 6 05/01/10 yyy

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

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 am trying to add confidence (error) bars to lattice barcharts (and dotplots, and xyplots). I found this helpful message from Deepayan Sarkar and based teh code below on it: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/50299.html However, I can't get it to work with groups, as illustrated. I am sure I am missing something elementary, but I am unsure what. Using R 2.1.1 on various

Hi all, I have data size of : > dim(sample) [1] 35943 17 The first column is "stdate" - is date ( 01/11/2009 00:00:00,02/11/2009 00:00:00,02/11/2009 00:00:00 etc... ) Login is 13th column - is numbers (12,0,1 erc...) The below operation return the following error. > sample1 <- read.csv(file="sample1.csv",sep=",",header=TRUE) > avglog <-

Hi, I have newbie question. Suppose I have the following data: temp <- data.frame(type1 = c("male", "female", "male", "female", "female"), type2 = c("low", "med", "high", "low", "med"), a = c(1,2,4, NA, 3), b = .... [TRUNCATED] temp type1 type2 a b c 1 male low 1 5 0 2 female

Hi there, > Value=c(709,679,699,657,594,677,592,538,476,508,505,539) > Lard=rep(c("Fresh","Rancid"),each=6) > Gender=rep(c("Male","Male","Male","Female","Female","Female"),2) > Food=data.frame(Value,Lard,Gender) > Food Value Lard Gender 1 709 Fresh Male 2 679 Fresh Male 3 699 Fresh

Hello, Say I have 2 columns, bmi and gender, the first being all the values and the second being male or female. How would I subset this into males only and females only? I have searched these fora and read endlessly about select[] and split() functions but to no avail. Also the table is not ordered. bmi gender -> bmi gender + bmi gender 1 24.78 male

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, 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

Dear R users, I have a problem, which I can not find a solution. Probably someone could help me? I have a result from my classification, like this > credit.toy [[1]] age married ownhouse income gender class 1 20-30 no no low male good 2 40-50 no yes medium female good [[2]] age married ownhouse income gender class 1 20-30 yes yes high male

I might have factored the gender. I'm not sure it would in any way be quicker. But might be to some extent easier to develop variations of. And is sort of what factors should be doing... # make dummy data gender <- c("Male", "Female", "Male", "Female") WC <- c(70,60,75,65) TG <- c(0.9, 1.1, 1.2, 1.0) myDf <- data.frame( gender, WC, TG ) #

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 =

I am trying to automate a report that my company does every couple of years for the state of Maine. In the past we have used SPSS to run the data and then used complicated Excel template to make the tables/graphics which we then imported into Word. Since there are 256 tables/graphics for this report, this work flow is a little painful. I would like to automate the process and I think I can do

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)

Hi R users, I am trying to extract some attributes (age, sex, area) from dataframe "AB" that has 101,269 observations of 28 variables to dataframe "t2" that has 47 observations of 6 variables. They share a column called "id", which is a factor with 47 levels. I want to end up with a dataframe that has 47 observations of 9 variables (the original 6 variables of t2,

>>>>> Paul Johnson <pauljohn32 at gmail.com> >>>>> on Fri, 16 Jun 2017 11:02:34 -0500 writes: > On Fri, Jun 16, 2017 at 2:35 AM, Joris Meys <jorismeys at gmail.com> wrote: >> To extwnd on Martin 's explanation : >> >> In factor(), levels are the unique input values and labels the unique output >>

Hi, This code is trying to produce a series of graphics files, with plots of male and female disease rates by age, one plot per disease. The dataframe contains a variable 'Age' and a set of variables called 'Male_CVD, Female_CVD,Male_RTA,Female_RTA, and so on. For each disease, I want to pull out the column of data containing the word 'Male' and plot this against age, and then

Hi, I have a data set similar to the following State Gender Quantity TX Male 1 NY Female 2 TX Male 3 NY Female 4 I need to calculate cumulative sum of the quantity by State and Gender. The expected output is State Gender Quantity CumQuantity TX Male 1 1 TX Male 3 4 NY Female 2 2 NY Female 4 6 I highly appreciate if someone can give me some hints on solving that in R. Hao -- View this