similar to: Importing csv files

I have Excel files containing data that I would like to move to R. They are in the standard form of a one row header followed by rows of data, one record per row EXCEPT that there are a few rows of comments before the header. The number of rows of comments varies. For Excel files of this form without comments I have had success with: require(RODBC) z <-

HI R lovers, I have been facing a petty trouble with datas' import : I have a plain txt file (see attached file or the copy below) that I cannot read either with scan or read.table > scan(file="F:/Alt/HDG/Stoliaroff/Data/test.txt") Error in scan(file = "F:/Alt/HDG/Stoliaroff/Data/test.txt") : "scan" expected a real, got "??6" >

Thanks to all who have responded. My concern was to be able to write a csv file that can have line feeds in string columns chr(10). Why? Excel allows line feeds chr(10) within cells and line breaks chr(13)+chr(10) at line ending, but the windows version of R automatically replaces \n by \r\n in writing and \r\n by \n in reading (text mode). The clues for a solution came from Brian Ripley and

Is there any documentation on what kind of SPSS file can and cannot be read by read.spss? Alternatively, how can one modify or "clean" an SPSS file to make it readable by read.spss? What properties must a *.sav file before read.spss can read it? The file in this example is 270KB, with 5 rows and 173 columns. I have no trouble reading larger files with read.spss, so it's not

Is there a dataload utility for linux. The link in genstat is down but I managed to find the utility at: http://gurukul.ucc.american.edu/econ/gaussres/UTILITYS/DATALOAD.HTM but this is a dos/windows version. Thank you Jean

I would like to announce that my DataLoad utility which can be found at: http://www.vsn-intl.com/genstat/downloads/datald.htm has been updated to support R data.frames. DataLoad reads a large variety of data formats (listed on the web page) and can convert these to ASCII or XDR data.frames. Only the Windows and Linux versions are up to date due to the fact that I no longer has access to a Unix

I tried to build the gold plugin and receive the errors posted below. I checked out the gold plugin using "cvs -z 9 -d :pserver:anoncvs at sourceware.org:/cvs/src co src," as documented on llvm.org. Is that version bleeding edge and perhaps not stable? The first errors have to do with the libtool version. I have libtool 2.2.6 on my system, which is what the README-maintainer-mode

Hello I try to fit a LDA and RDA model to the same data, which has two classes. The problem now is that the training errors of the LDA model and the training error of the RDA model with alpha=0 are not the same. In my understanding this should be the case. Am I wrong? Can someone explain what the reason for this difference could be? Here my code: LDA model: =========== % x is a dataframe tmp =

If save() fails because an object is not found, it should not overwrite an existing file. > a <- 1:9 > save(a, file = "a.rda") > rm(a) > load("a.rda") > a [1] 1 2 3 4 5 6 7 8 9 > rm(a) > save(a, file = "a.rda") Error in save(a, file = "a.rda") : object 'a' not found > load("a.rda") Error in

The attached patch to the qemu emulation of the pcnet hardware fixes several problems. It will now only read and write a transmit or receive descriptor once. It will correctly handle transmitting frames with more than two fragments. It will discard oversize frames instead of corrupting memory. I have tested all the changes I have made and even seen an improvement in receive performance from

I'm encountering excruciatingly slow load times for character vectors in R 2.6.0-- up to 30sec for a 15K file that contains a no-attributes character vector of length ~1e4 and object size ~0.5MB. In R 2.5.1, repeated loads of the same set of files are near-instantaneous. The problem is proving tricky to reproduce consistently from scratch, so I have attached the 3 files used in the examples

Dear all, I'm performing RDA on plant presence/absence data, constrained by geographical locations. I'd like to constrain the RDA by the "extended matrix of geographical coordinates" -ie the matrix of geographical coordinates completed by adding all terms of a cubic trend surface regression- . This is the command I use (package vegan): >rda(Helling ~

I've got something that might be a clue to understand the strange behaviour of lda in R --gui="gnome": in R --vanilla: library(MASS) load("mod23puriflda.rda") > a <- lda.default(x=mod23puriflda[,2:5],grouping=mod23puriflda[,6],CV=F) works fine. I save lda.default as a local rda file: > milda.nognome <- lda.default >

I've tried a few things both with prcomp(), and rda() and its friends in vegan (including biplot.rda and ordiplot), but can't find a solution. I'd like to associate subsets of the points in a resulting biplot ("sites" in the rda object) with different plotting colors/text styles to emphasize certain sets of points. I can't figure out how to keep the arrows (for

Hi Everybody I use R2.8.0 on Mac OS X. I set up LyX 1.6.1 to use Sweave today. I can compile the test file I found on CRAN ( http://cran.r-project.org/contrib/extra/lyx/) without a problem and the output looks very nice. In the test file the following R code is used. <<myFirstChunkInLyX>>= xObs <- 100; xMean <- 10; xVar <- 9 x <- rnorm(n=xObs, mean=xMean, sd=sqrt(xVar))

Hello R user, I have four data sets in dir "D:/Bharat Warule/Rdata_file" which are output_data_prod_1.rda, output_data_prod_2.rda, output_data_prod_3.rda, output_data_prod_4.rda. Each data set is huge size like number of rows 343297 and columns are near to 50. For example: x1 <- data.frame(x11=c(1,2,3,4,5),x112=c(10,10,10,10,10)) x2 <-

Dear all, I did a RDA and when I looked to the signification of the test with permutest, the output was non-significant. But when I used the envfit function, some of the vectors are significant. All the test's conditions are respected. What it means? Is it an error in the script? Commands and output: > permutest(rda.ind, perm=999, first=TRUE) Permutation test for rda  Call:

R-1.4.0 seems to have changed the way delay() works, or perhaps it is the way library() works that nullifies the advantages of using delay() in a package. It seems that the process of loading a package evaluates each object provided by that package, and so in particular, the delay()ed object is evaluated and brought into memory. For example generating a test example, where test/R/functions.s is:

Dear developeRs, my package FrF2.catlg128 holds large catalogues and is supposed to gain additional ones. All the catalogues are intended for the user. So far, the catalogues were stored in the data directory, and LazyData was "no". I understand that this is not considered wise any more (if it ever was), so that I want to change to LazyData "yes" with the next release

Dear All: It was saved, but there was a space somewhere. So it works for me now. I do have another similar problem. I saved an R data file save(datahs0csv,file=" F:\Fall_2017\5-STA574\2-Notes\1-R\1-R_new\chapter4-Entering_Data/datahs0csv2 .rda") *The new R data file "*datahs0csv2.rda*" is in the directory.* I tried to load the file "" to R, but I got an error