similar to: Error in names(x) <- value: 'names' attribute must be the same length as the vector

Hello, Everybody: This may not be a "bug", but for me it is an unexpected outcome. A factor variable's levels do not retain their ordering after the levels function is used. I supply an example in which a factor with values "BC" "AD" (in that order) is unintentionally re-alphabetized by the levels function. To me, this is very bad behavior. Would you agree? #

Suppose plotx <- "someName" modx <- "otherName" plotxRange <- c(10,20) modxVals <- c(1,2,3) It often happens I want to create a dataframe or object with plotx or modx as the variable names. But can't understand syntax to do that. I can get this done in 2 steps, creating the data frame and then assigning names, as in newdf <- data.frame( c(1, 2, 3, 4),

How does one remove a column from a data frame when the name of the column to remove is stored in a variable? For Example: colname <- "LOT" newdf <- subset(olddf,select = - colname) The above statement will give an error, but thats what I'm trying to accomplish. If I had used: newdf <- subset(olddf,select = - LOT) then it would have worked, but as I said the column

I'm pasting below a working R file featuring a function I'd like to polish up. I'm teaching regression this semester and every time I come to something that is very difficult to explain in class, I try to simplify it by writing an R function (eventually into my package "rockchalk"). Students have a difficult time with predict and newdata objects, so right now I'm

Hi all, I still have problems with the predict function by setting up the values on which I want to predict ie: original df: p1 (193 obs) variates y x1 x2 rm(list=ls()) x1<-rnorm(193) x2<-runif(193,-5,5) y<-rnorm(193)+x1+x2 p1<-as.data.frame(cbind(y,x1,x2)) p1 y x1 x2 1 -0.6056448 -0.1113607 -0.5859728 2 -4.2841793 -1.0432688 -3.3116807 ...... 192

I have a data frame with 155,000 rows. One of the columns represents the user id (of which about 10,000 are unique). I am able to isolate 1000 of these user ids (stored in a list) that I want to eliminate from the data set, but I don't know of an efficient way to do this. Certainly this would be slow: newdf<-df for(i in listofbadusers) { newdf<-subset(tmp,uid!=i) } is there a better

Hi, I have two lists (c and h - see below) containing matrices with similar cases but different values. I want to split these matrices into multiple matrices based on the values in h. So, I did the following: years<-c(1997:1999) for (t in 1:length(years)) { year=as.character(years[t]) h[[year]]<-sapply(colnames(h[[year]]), function(var)

Hi all, Very surprising (to me!) and mystifying result from predict.glm(): the predictions vary depending on whether or not I use ns() or splines::ns(). Reprex follows: library(splines) set.seed(12345) dat <- data.frame(claim = rbinom(1000, 1, 0.5)) mns <- c(3.4, 3.6) sds <- c(0.24, 0.35) dat$wind <- exp(rnorm(nrow(dat), mean = mns[dat$claim + 1], sd = sds[dat$claim + 1])) dat <-

OK, I need help!! I've been searching, but I don't understand the logic of some this dataframe addressing syntax. What is this type of code called? test [["v3"]] [is.na(test[["v2"]])] <-10 #choose column v3 where column v2 is == 4 and replace with 10 and where is it documented? The code below works for what I want to do (find the non-missing value in a row),

On Sat, 15 Jul 2017, Michael Reed via R-help wrote: > Dear All, > > I need some help arranging data that was imported. It would be helpful if you were to use dput to give us the sample data since you say you have already imported it. > The imported data frame looks something like this (the actual file is > huge, so this is example data) > > DF: > IDKey X1 Y1 X2 Y2

Problems with predict and lines in plotting binomial glm Dear R-helpers I have found quite a lot of tips on how to work with glm through this mailing list, but still have a problem that I can't solve. I have got a data set of which the x-variable is count data and the y-variable is proportional data, and I want to know what the relationship between the variables are. The data was

Dear All, I need some help arranging data that was imported. The imported data frame looks something like this (the actual file is huge, so this is example data) DF: IDKey X1 Y1 X2 Y2 X3 Y3 X4 Y4 Name1 21 15 25 10 Name2 15 18 35 24 27 45 Name3 17 21 30 22 15 40 32 55 I would like to create a new data frame with the following NewDF: IDKey X Y Name1 21 15 Name1

Greetings all: OK, this is bugging the @#@%* out of me. I know the answer is simple and straightforward but for the life of me I cannot find it in the documentation, in the archives, or in my notes (because I know I've encountered this in the past). My problem is: I have a data frame with columns A, B, C, D, and E. A, B, and E are factors and C and D are numeric. I need a new data frame with

I have the following data frame: > foo w x y z n 1.51550092 1.4337572 1.2791624 1.1771230 q 0.09977303 0.8173761 1.6123402 0.1510737 r 1.17083866 1.2469347 0.8712135 0.8488029 What I want to do is to change it into : > newdf 1 n w 1.51550092 2 q w 0.09977303 3 r w 1.17083866 4 n x 1.43375725 5 q x 0.81737606 6 r x

Hi, How can I achieve this in R. Dataset is as follows: >df x 1 2 2 4 3 1 4 3 5 3 6 2 structure(list(x = c(2, 4, 1, 3, 3, 2)), .Names = "x", row.names = c("1", "2", "3", "4", "5", "6"), class = "data.frame") I want to recreate a new data frame whose rows are sum of (1&2, 3&4, 5&6)

I'm trying to run a function inside a function but get an error message. lst <- list(roots = c("car insurance", "auto insurance"), roots2 = c("insurance"), prefix = c("cheap", "budget"), prefix2 = c("low cost"), suffix = c("quote", "quotes"), suffix2 = c("rate", "rates"), suffix3 =

Last Friday, I noticed that it is difficult to work with regression models in which there are factors. It is easier to do the old fashioned thing of coding up "dummy" variables with 0-1 values. The predict function's newdata argument is not suited to insertion of hypothetical values for the factor, whereas it has no trouble with numeric variables. For example, if one uses a

Hello I have 2 data frames DF1 and DF2 where DF2 is a subset of DF1: DF1= data.frame(V1=1:6, V2= letters[1:6]) DF2= data.frame(V1=1:3, V2= letters[1:3]) How do I create a new data frame of the difference between DF1 and DF2 newDF=data.frame(V1=4:6, V2= letters[4:6]) In my real data, the rows are not in order as in the example I provided. Thanks much Joseph [[alternative HTML version

I have a site on a shared host at TextDrive. I have an import process that imports a CSV file into the database using a ruby script executed using script/runner. TextDrive has a memory limit which I am hitting and the process gets killed. I get through to about 400 records before it dies. I guess each time I instantate a new object for each record I am using more memory but thought I was using

Hi Eric,Thanks for the explanation. Is there a way to save the results automatically after the analysis gets over?. As I recently lost the results, because I didn't save the results. I don't want to run the sink or save command after the analysis is over rather run the command for saving the file before starting to run the analysis, so the file gets saved automatically after the script has