similar to: summary of categorical variables

Dear list, first accept my apologies for asking a non-R question. Can anyone point me to a good reference on logistic regression? web or book references would be great. I am interested in the use and interpretation of dummy variables and prediction models. I checked the contributed section in the CRAN homepage but could not find anything (Julian Faraway?s "practical Regression and ANOVA

Dear list, this must be an easy one: I have a data.frame of two columns, "ID" with four different levels (A to D) and numerical "size", and each of the 4 different IDs is repeated a different number of times. I would like to get the mean size for each ID as another data.frame. I have tried the following: >ID= as.character(unique(data[,1])) # I use unique() because

Dear list Is there anywhere I could find further information on how to interpret the output for a logistic regression for validate() from Design package?. I tried ?validate and google but I cannot find information on what the rows and the columns represent. Thanks David

Dear list, first apologies for this is not strictly an R question but a theoretical one. I have read that use of k-means clustering assumes sphericity of data distribution. Can anyone explain me what this means? My statistical background is too poor. Is it another kind of distribution, like gaussian or binomial? What does it happen if the distribution is not spherical? Could you give me an

Dear list I would like to compare two measurements of disease severity (M1 and M2), one of the is continuous (M1 ranging from 1 to 10) and the other is ordinal (M2 takes Low, Medium, high and very high). Do you think is ok to use cor() function to test whether the two agree, i.e correlate? I am afraid that if I set M2 to 1,2,3 and 4, the function cor() will take them as continuous and

Dear list, I have a categorical variable in a data.frame that I would like to plot using a histogram to show number of events. Values are 0, 1 and some NAs. I can?t make the hist() function to 1) include a column with the number of NAs 2) have the x axis to be categorical, I always get 0, 0.2, 0.4,... 1 divisions Can anyone help me? This is my code. "database" is my data.frame and

Dear list, I have a text file from a scanner that includes 20 lines of text (scanner settings) before it actually starts showing the readings in a tabular format (headings are ID, intensity, background and few others). I am a biologist with some experience using R and my question is if it is possible to read this file into an R workspace and store the actual readings in a dataframe,

It?s sometimes faster to ask from someone who has already learnt the syntax. In this case one has to do e.g. names(data$somecol) To get the collection and then iteration through it is almost like in Python: for(i in names(data$somecol)) { # do something } > Bert Gunter <bgunter.4567 at gmail.com> kirjoitti 6.11.2017 kello 19.55: > > Time to go through a tutorial or two! --

Matti - Since you are asking about looping through a column, not looping across columns, it is simply the following: # Note: data.frame() turns strings into factors by default. myDF <- data.frame(type = c("a", "j", "a", "a", "j"), weight = c(12.3, 6.8, 10.5, NA, "5.5")) myDF$type # ... is a vector of factors

Hello, If you want to loop through the columns of a data.frame you can do for(i in names(df)){ [code] } Another way would be lapply(names(df), function(somecol) class(df[[somecol]])) where class(df[[somecol]]) is just an example, you would use whatever fits your needs. When you say that the column in question holds "levels" do you mean it's a factor? (factors are R's

Boris: "As others have remarked, for added efficiency with large datasets we often use functions from the apply() family, rather than for-loops." That is generally false, though it is a common misconception. Apply-type functions are used to maintain fidelity -- and for some, clarity -- to a functional programming paradigm. Cheers, Bert Bert Gunter "The trouble with having an

Dear all, I?m having trouble getting a list of regression variables back into a dataframe. mydf <- data.frame(x1=rnorm(100), x2=rnorm(100), x3=rnorm(100)) mydf$fac<-factor(sample((0:2),replace=T,100)) mydf$y<- mydf$x1+0.01+mydf$x2*3-mydf$x3*19+rnorm(100) dlply(mydf,.(fac),function(df) lm(y~x1+x2+x3,data=df))->dl here I?d like to use ldply(dl,coef(summary)) or something

I apologize for my constant questions but I am new to R and trying to gain an appreciation for its capabilities. The following task is easy in Excel and I was hoping somebody could give me a quick explanation for how it can be acheived in R so I can avoid having to switch between the two applications. How do I find the Summary Statistics in one Vector of the dataframe by levels in another of the

I am getting an error when trying to import tab delimited .txt file saved from Excel. I have read what is posted on the forums but still am confused. I saved my Excel file (DataTestforR.xlsx) as a tab delimited txt file (DataTestR.txt) on my Desktop. In the RGUI, I tried to import the txt file and got an error > myfile<-"C:\\Users\\jpapa\\Desktop\\DataTestR.txt" >

I have a two question regarding the "aggregate.data.frame" method of the "aggregate" function. My situation: a. My "x" variable is a data.frame ("mydf") with two columns, both columns of type/format "numeric". b. My "by" variable is a data.frame("mybys") with two columns, both columns of type/format "character". c.

I'm new to R and struggling to reproduce graphs I've made with gnuplot. Example here: http://www.slamb.org/tmp/one-active.png I have three different data sets plotted on the same axis. (I also have a number of samples for each X value which I displayed with quartiles rather than plotting every point; that will likely be the subject of my next question.) My attempts to do this in R:

Dear list people Suppose we have a data.frame where variables are categorical and the response is categorical eg: my.df=NULL for(i in LETTERS[1:3]){my.df[[i]]=sample(letters, size=10)} my.df=data.frame(my.df) my.df$class=factor(rep(c("pos", "neg"), times=5)) my.glm=glm(class ~ ., data=my.df, family=binomial) summary(my.glm) .... Estimate Std. Error z

Just a minor point in the suggested solution: df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) since WC and TG are not conditional, would this be a slight improvement? df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58))) -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via R-help Sent: Friday,

I would like to know if someone has done work on trees with multivariate response. I need something like rpart but for vector responses. If someone has code that he/she is willing to share, I would be grateful. If not, even guidelines for writing my own starting from rpart would be welcomed. ft. -- Fernando TUSELL e-mail: Departamento de

Hi All I have a datafram which looks like this : CustomerID DietType 1 a 1 c 1 b 2 f 2 a 3 j 4 c 4 c 4 f And I would like to reshape this so I can