similar to: duplicates() function

I'd like to remove duplicated rows within a matrix, with missing data being treated as wildcards. For example > x <- matrix((1:3), 5, 3) > x[4,2] = NA > x[3,3] = NA > x [,1] [,2] [,3] [1,] 1 3 2 [2,] 2 1 3 [3,] 3 2 NA [4,] 1 NA 2 [5,] 2 1 3 I would like to obtain [,1] [,2] [,3] [1,] 1 3 2 [2,] 2 1 3

Hi All, I have a 75GB collection of data, including a lot of duplicated files, on a NTFS network drive. I want to backup that data across a DSL link to a Linux host. Currently I use cwrsync on a Windows machine to act as server to the Linux rsync client. I want to avoid transferring duplicated data, as the DSL link is a far more significant factor than computation/disk IO. I can't work

Hi everybody. I want to identify not only duplicate number but also the original number that has been duplicated. Example: x=c(1,2,3,4,4,5,6,7,8,9) y=duplicated(x) rbind(x,y) gives: [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] x 1 2 3 4 4 5 6 7 8 9 y 0 0 0 0 1 0 0 0 0 0 i.e. the second 4 [,5] is a duplicate. What I want is

Dear R family, Suppose I have two series. order value 1 0.52 2 0.23 3 0.43 4 0.21 5 0.32 6 0.32 7 0.32 8 0.32 9 0.32 10 0.12 11 0.46 12 0.09 13 0.32 14 0.25 For these two series, I figured out the way to detect the locations of duplicate values. The next thing to do is remove the repeated values except for a value that would not be next to each other. In other words, while keeping the

hey guys, I am working on a function to make a duplicated value unique. For example, the original vector would be like : a = c(2,1,1,3,3,3,4) I'll like to transform it into: a.nodup = 2, 1.01, 1.02, 3.01, 3.02, 3.03, 4 basically, find the duplicates and assign a unique value by adding a small amount and keep it in order. I come up with the following codes, but it runs slow if t is large. Is

Hei R Users, i have the following dataframe: Datetime Temperature and many more collumns 1 2008-6-1 00:00:00 5 2 2008-6-1 02:00:00 5 3 2008-6-1 03:00:00 6 4 2008-6-1 03:00:00 0 5 2008-6-1 04:00:00 6 6 2008-6-1 04:00:00 0 7 2008-6-1 05:00:00 7 8 2008-6-1 06:00:00

On Tuesday 06 February 2001 12:36, Dr. Jens Oehlschlägel wrote: > I like the idea. Why don't you call duplicated.matrix() directly in > unique.matrix() and duplicated.data.frame() in unique.data.frame() ? > > Jens Oehlschlägel Good point. I guess I got carried away with using methods (having just gotten the hang of the concept). :-) Anyway, here's a corrected version:

Dear all, Sorry for the simplicity of the question, but how does one go about removing duplicated rows in a data.frame? I'm looking for a quick and simple solution, as my data.frames are relatively large (50000 by 50). I've racked my brain and searched the help files and found nothing useful or quick, only duplicated() and unique() which work only work on lists. Thanks Gary.

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,

Hello, Given a vector I would like to rapidly identify duplicated non contiguous elements. Given for example c(1, 1, 2, 3, 2, 4, 5, 6, 4) I would like to get: FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE TRUE In fact I need to check this on the columns of a matrix! I can do that of couse with loops but is there any function already available? Thanks

Hi, I'm new to R, and I'm STATA user before, could you help me where I can get document about comparison command between STATA and R. Thank you very much, Best regards, -iip-

Hi all, I have a relationship (no really!) class RiskMatrix < ActiveRecord::Base has_many :severities, :order => :position, :uniq => true end class RiskFactor < ActiveRecord::Base belongs_to :risk_matrix validates_presence_of :descriptor, :example validates_uniqueness_of :descriptor, :example, :scope=> :risk_matrix_id end class Severity < RiskFactor

I am using the package nlme to fit a simple random effects (variance components model) with 3 parameters: overall mean (fixed effect), between subject variance (random) and within subject variance (random). I have 16 subjects with 1-4 obs per subject. I need a 3x3 variance-covariance matrix that includes all 3 parameters in order to compute the variance of a specific linear

List, I want to reshape my data, but I'm not sure how to do it... it might be a simple task, but don't know which package does this. "occ.data" (see below) is how my original data are arranged, and I know that with melt() I can reshape it like "y" (see below). However, I just want to build a matrix like the "y" matrix, but with only 2 dimensions. Something

Hi guys, I need some help to analyzing my data. I start to describe my data: I have 21 matrices, every matrix on the rows has users and on columns has items, in my case films. Element of index (i, j) represent the rating expressed by user i about item j. I have a matrix for each of professions. An example of a this type of matrix is: item 1 item 2 item 3 item4 id

Dear all, As part of a larger function, I am randomly removing rows from a data frame. The number of removed rows is determmined by a Poisson distribution with a low mean. Sometimes, the random number is 0, and that's when the problem starts: My data frame: > temp occ x y dbh age 801 0 2977.196 3090.225 6 36.0 802 0 2951.892 3083.769 8 40.6 803 0 2919.111

Dear all The trouble with the current duplicated() function in is that it can report duplicates while searching fromFirst _or_ fromLast, but not both ways. Often users will want to identify and extract all the copies of the item that has duplicates, not only the duplicates themselves. To take the example from the man page: > data(iris) > iris[duplicated(iris), ] ##duplicates while

Hi all, I am a new user for R. I faced a questions about subscript out of bounds. Although I checked some other helps before I sent this email, I still don't know how to deal with this problems. I want to use "domain" function to run species distribution model in R. I used "sp.occ.do<-domain(env.pre, pred_train, factors=c('continent')) &

Hi All, I have a doubt. I used macros and i try to pass a value to a macro by concatenating a bunch of strings. But it does not seem to work. Please help. I have written down my code and the error message please tell me how to pass the value that a string points to. Thanks in advance #macro defined

I am in the process of transferring from an old version of S+ to using R having used a variety of other packages in the past. I'm hugely impressed with R but it has an excellent but depressing habit of exposing that I'm not a professional statistician and has done so again. Someone has run a nice little repeated measures design on my advice, students randomised to four orders of a