similar to: Selecting cases from matrices stored in lists

Hi list, based on the following data.frame I would like to create a variable that indicates the number of occurrences of A in the 3 years prior to the current year: DF = data.frame(read.table(textConnection(" A B 8025 1995 8026 1995 8029 1995 8026 1996 8025 1997 8026 1997 8025 1997 8027 1997 8026 1999 8027 1999 8028 1995 8029 1998 8025 1997 8027 1997 8026 1999 8027 1999

Hi, I have produced a list g and I would like to reduce the amount of information contained in each object in g. For each matrix I would like to keep the values where the column name equals g[year][[1]][[x]] and the row names equals g[year][[1]][[-x]]. So in g$`1999`$`8029`, year = 1999 and x = 8029. I have been experimenting with the subset function, but have been unsuccesful. Thanks for your

Hi, I have a question concerning the selection of data. Let's say that given list h created below, I would like to select a section of the 1999 matrix. For a case (rownames and colnames) I would like to select the cells that have a value > 0. So for case 8025 8025 8026 8027 8025 1 1 1 8026 1 1 1 8027 1 1 1 And for case 8028 8028 8029 8028 1

Hi list, Can anyone tell my why the following does not work? Thanks a lot! Your help is very much appreciated. DF = data.frame(read.table(textConnection(" B C D E F G 8025 1995 0 4 1 2 8025 1997 1 1 3 4 8026 1995 0 7 0 0 8026 1996 1 2 3 0 8026 1997 1 2 3 1 8026 1998 6 0 0 4 8026 1999 3 7 0 3 8027 1997 1 2 3 9 8027 1998 1 2 3 1 8027 1999

Hi list, I would like to use the following data.frame to generate matrices over a 3 year moving window: DF = data.frame(read.table(textConnection(" A B C 80 8025 1995 80 8026 1995 80 8029 1995 81 8026 1996 82 8025 1997 82 8026 1997 83 8025 1997 83 8027 1997 84 8026 1999 84 8027 1999 85 8028 1995 85 8029 1998"),head=TRUE,stringsAsFactors=FALSE)) Function to be

Hi list, Using the script below, I have generated two lists (c and h) containing yearly matrices. Now I would like to divide the matrices in c into multiple matrices based on h. The number of matrices should be equal to: length(unique(DF1$B))*length(h). So each unique value in DF1$B get's a yearly matrix. Each matrix should contain all values from c where element cij is 1. An example for

Hi, I am trying to use the objects from the list below to create more objects. For each year in h I am trying to create as many objects as there are B's keeping only the values of B. Example for 1999: $`1999`$`8025` B B 8025 8026 8027 8028 8029 8025 1 1 1 0 0 8026 1 0 0 0 0 8027 1 0 0 0 0 8028 0 0 0 0 0 8029

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),

Dear R-helpers, I am stuck on an error in R: When I run my code (below), I get this error back: Error in names(x) <- value : 'names' attribute must be the same length as the vector Then when I use traceback(), R gives me back this in return: `colnames<-`(`*tmp*`, value = c(""Item", "Color" ,"Number", "Size")) I'm not exactly

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 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