similar to: Creating objects (data.frames) with names stored in character vector

Dear all, I have searched the forums for an answer - and there is plenty of questions along the same line - but none of the paproaches shown worked to my problem: I have a data frame that I get from a csv: summarystats<-as.data.frame(read.csv(file=f_summary)); where I have the columns Dataset, Class, Type, Category,.. Problem1: I want to find a subset of this frame, based on values in

Hello, I have been banging my head against the wall trying to figure out this seemingly simple problem with no success. I'm hoping that one or some of you can help. Here is the code I am trying to use: #importing data data.file <-read.csv("/file/location", header=TRUE, sep = ",") #selecting a subset of data based on variable "Sample" data.subset1 <-

Hi, In the code below I create a small data.frame (dat) and then cut it into different groups using CutList. The lists in CutList allow to me choose whatever columns I want from dat and allow me to cut it into any number of groups by changing the lists. It seems to work OK but when I'm done I have a variable number of data frames what I need to do further operations on and I don't know

Hi R-devel, I am facing a situation where the number of options I would like to propose to the user is somewhat big (and could easily increase more and more as I will code up a little more - even coming to a point where an user should be able to implement his own options). What we have to handle options is the couple: options(par=value) and getOption("par") I was aking myselft what

Hi, I''m having a dataframe ''Subset1'' with a number of factor variables and 160 numerical variables Now I want to make sums for all rows that have the same values for the different factor variables, except for the factor variables: VAR1,VAR2,VAR3 who may have the same values. With the formula given below this works great, but in a situation with 15000 rows and 13

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:

Hi, I'm wondering why indexing a data frame by row name doesn't work with [[. It works with [: > sw <- swiss[1:5,1:2] > sw["Moutier", "Agriculture"] [1] 36.5 but not with [[: > sw[["Moutier", "Agriculture"]] Error in .subset2(.subset2(x, ..2), ..1) : subscript out of bounds The problem is really with the row name (and not

Consider in R-2.6.0 (also R-patched from yesterday): iris[1, c(TRUE, FALSE, FALSE, FALSE, FALSE)] ## Error in .subset2(xx, j) : recursive indexing failed at level 2 iris[1, c(FALSE, FALSE, FALSE, FALSE, TRUE)] ## Error in .subset2(xx, j) : attempt to select less than one element i.e. matrix-like indexing on data.frames, one logically-indexed dimension with only one value TRUE in it. It is

Below is a version of [.data.frame that is faster for subscripting rows of large data frames; it avoids calling duplicated(rows) if there is no need to check for duplicate row names, when: i is logical attr(x, "dup.row.names") is not NULL (S+ compatibility) i is numeric and negative i is strictly increasing "[.data.frame" <- function (x, i, j,

Hi, Hope you are well. I was wondering if there is a function at C level that is equivalent to mtcars$carb or .subset2(mtcars, "carb"). If I have the index of the column then the answer would be VECTOR_ELT(df, asInteger(idx)) but I was wondering if there is a way to do it directly from the name of the column without having to loop over columns names to find the index? Thank you Best

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Dear all, I am encountering problems with the application of ddply within the body of a self-defined function. The script is the following: moncostcarmoto <- function(costtype){ costaux_result <- data.frame() for (purp in PURPcount){for (per in PERcount){ costcarin =

Hello, I am trying to run the APE program COMPAR.GEE with a model containing a categorical response variable and a mixture of continuous and categorical independent variables. The model runs when I have categorical (binary) response and two continuous independent variables (VAR1 and VAR2), but when I include a categorical (binary) independent variable (VAR3), I receive the following output with

Hello there, I am not quite sure how to interpret the output of Rprof (in the following the output I was staring at). I was poking around the web a little bit for documentation but without much success. I guess if I want to figure out what takes so long in my code the 2nd table $by.total and the total.pct column (pct = percent) is the most helpful. What does it mean that [ or [.data.frame is

Short: get rid of the loops I use and optimize runtime Dear all, I want to calculate for each row the amount of the month ago. I use a matrix with 2100 rows and 22 colums (which is still a very small matrix. nrows of other matrixes can easily be more then 100000) Table before Year month quarter yearmonth Service ... Amount 2009 9 Q3 092009 A ...

Hello. I'm currently trying to wrap up data frames into OCaml via OCaml-R, and I'm having trouble with data frame subsetting: > # x#column 1;; > Erreur dans (function(x, i, exact) if (is.matrix(i)) as.matrix(x)[[i]] else .subset2(x, : > l'?l?ment 1 est vide ; > la partie de la liste d'arguments de 'is.matrix' en cours d'?valuation ?tait : > (i)

Hi, Here seems to be a corner case in which format() fails: > format(data.frame()) Error in .subset2(x, i, exact = exact) : subscript out of bounds > sessionInfo() R version 3.0.2 (2013-09-25) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8

Is there a low-level function that returns the length of an object 'x' - the length that for instance .subset(x) and .subset2(x) see? An obvious candidate would be to use: .length <- function(x) length(unclass(x)) However, I'm concerned that calling unclass(x) may trigger an expensive copy internally in some cases. Is that concern unfounded? Thxs, Henrik

Hi, I often use plotmeans() from the gplots package to quickly visualize a pattern of change. I would like to be able to plot separate lines for different groups, but the function gives an error when a grouping variable is included in the formula argument. For instance, > require(gplots) > x <- data.frame(Score=rnorm(100), Time=rep(1:10, 10),

One of my colleagues has a data set from a two-level nested design from which we would like to estimate variance components. But we'd like some idea of what the inevitable outliers are doing, so we were looking for something in R that uses robust (eg Huber) treatment and returns robust estimates of variance. Nothing in my collection of R robust estimation packages (robust, robustbase and MASS