similar to: dummy variable encoding

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 all, I used "which" to obtain a subset of values from my data.frame. however, I find that there is a "trace" of the values I have removed. Any suggestions would be greatly appreciate. Below is my data: d <- data.frame( val = 1:10, group = sample(LETTERS[1:5], 10, repl=TRUE) ) >d val group 1 1 B 2 2 E 3 3 B 4 4

I'm presumably missing something very obvious, but how does one use the key.opts argument in labcurve (via Ecdf)? In this example, I want the key to be big and have a blue background, but it isn't and doesn't. ch <- rnorm(1000, 200, 40) sex <- factor(sample(c('female','male'), 1000, TRUE)) Ecdf(~ch, group=sex, label.curves=list(keys=c("f",

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

Hey, Is it possible that R can calculate each options under each column and return a summary table? Suppose I have a table like this: Gender Age Rate Female 0-10 Good Male 0-10 Good Female 11-20 Bad Male 11-20 Bad Male >20 N/A I want to have a summary table including the information that how many answers in each category, sth like this: X

Hi all, I have the following x1<-paste("A", 1:6, sep = "") x2<- round(rgamma(6,2,1)) x3<-paste("B", 1:6, sep = "") x4<- round(rgamma(6,2,1)) data1 <- data.frame(x1,x2,x3,x4) I would like to get data2 <- c(A1=4, A2=1, A3=0,...) Is there any standard for such a case? Thank you very much in advance, Diego

Hello there, I have two groups (men and women) and I know per group how many of them smoke or don't smoke (women 40 of 200; men 100 of 300). I would like to know how I can compare in R if men and women differ significantly in their smoking. However, because there are more men in the sample than women I cannot just compare the number of smokers and non-smokers in both groups, right?! (I would

Hello Helpers, I have some problems with fitting the model for my data... -->my Literatur says (crawley testbook)= Non-normality of errors-->I get a banana shape Q-Q plot with opening of banana downwards Structure of data: origin wt pes gender 1 wild 5.35 147.0 male 2 wild 5.90 148.0 male 3 wild 6.00 156.0 male 4 wild 7.50 157.0 male 5 wild 5.90

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 everyone, I get some data in the following format and I would like to combine them to form a dataframe. The data is like: cbcname1 = 0.1, cbcname2= 0.2, cbcname3=0.3,... name1, name2, name2 are just some random names. I would like to achieve sth like: (cbcname1=0.1, cbcname2=0.2, cbcname3=0.3,......) I am using the following codes do.call(cbind,

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 ) #

I want to run deconvolution of a time series by an impulse or point-spread function through Wiener filter, regularized filter, Lucy-Richardson method, or any other approaches. I searched the CRAN website and the mailing list archive, but could not find any package for such a deconvolution analysis. Does anybody know an existing R function for deconvolution? TIA, Gang

Hello, R friends, I'm trying to crack this nut: Example Data. pet    gender dog    male dog    female dog    male cat    female cat    female cat    male Plot Task. Horizontal 100% bars where y axis shows gender factor (male vs. female) and x axis shows percentage of kind of pets (dog vs. cat) so that % dogs + % cats are stacked in 1 bar and sum up to 100% (for each gender group 1

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 <-

ScopedProxy uses with_scope and proxy objects to make it easy to find and count different types of records. Example: class Person < ActiveRecord::Base scoped_proxy :minor, :conditions => ''age <= 17'' scoped_proxy :adult, :conditions => ''age >= 18'' scoped_proxy :old, :conditions => ''age >= 70'' scoped_proxy :male,

Hi all: My data has 3 variables: age(3levels : <30y=1 30-50y=2, >50y=3) gender(Male=0, Female=1) CD4 cell count(raw lab measurement) y(1:death 0:alive) I perform logistic regression to find out the factors that influence y. result<-glm(y ~ factor(age) + factor(gender) + CD4,family = binomial) >From the result,I can get OR(Odds Ratio) of gender via exp(Estimate of Female,

I have a question about how to filter the data frame: Suppose my data frame has variables like gender, age,... How to get a subset of the data frame, with only female (or male) and/or age > 50...? What is the typical syntax? I tried several condition expressions, but none of them worked... Thanks a lot! -- View this message in context:

I am trying to read an ftable using read.ftable, but I get the following error message: > jobSatTable <- read.ftable("http://definetti.uark.edu/~gpetris/stat5333/jobSatisfaction.dat",skip=2) Error in seek(file, where = 0) : no applicable method for "seek" In addition: Warning messages: 1: no non-missing arguments to max; returning -Inf 2: no non-missing arguments to

I apologize in advance if this is the wrong forum for this report/request, and for the fact that I have not read the code for ftable.formula in any detail. >From reading the documentation for ftable.formula, I expected that the following two calls to ftable would produce the same results: data(UCBAdmissions) ftable(UCBAdmissions, row.vars = "Dept", col.vars = c("Gender",

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