similar to: Difference in 'read.table' between R.1.4.1 and R1.5.0

Thanks a lot, James!! The problem is fixed. On the version 1.4.0 Mac/darwin (the latest available version for this system) the function read.table (which is called from read.delim etc., too) has the bug you explained. Inserting the row nlines <- nlines+1 after lines <- c(lines, line) removes this bug. M. On Friday, February 22, 2002, at 02:33 PM, james.holtman at convergys.com

Anyone have luck with pxechn32 and bootmgfw.efi? I'm getting the "Unable to retrieve first package" issue as reported by others. Really, any advice for UEFI booting into a winpe environment off of pxelinux 6.03 would be beneficial. Jason Jones Sr. Associate, Network Services | End User Computing 3947 N Oak St Ext | Valdosta, GA 31605 O +15137844955 E jason.s.jones at

The 'read.table' function appears to be up to 10X slower in R 1.4.0 than R 1.3.1 for some of the data sets I read in. I was comparing the source code for the 2 versions and see that it was rewritten in R 1.4.0. I think I found out what part of the problem might be. I was comparing R1.3.1 and R1.4.0 code and it appears that a statement is missing in some of the code for R 1.4. This is

Hi everyone, my apologies if I'm overlooking something obvious in the documentation. I'm relatively inexperienced with the (awesome) ff package. My goal is to use the read.table.ffdf() function to call the read.fwf() function and pass through the colClasses and comment.char arguments. The code below shows exactly what doesn't work for me. If the colClasses and comment.char

>>>>> Benjamin Tyner <btyner at gmail.com> >>>>> on Tue, 24 Oct 2017 07:21:33 -0400 writes: > Jeff, > Thank you for your reply. The intent was to construct a minimum > reproducible example. The same warning occurs when the 'file' argument > points to a file on disk with a million lines. But you are correct, my >

Hello, We've released the int64 package to CRAN a few days ago. The package provides S4 classes "int64" and "uint64" that represent signed and unsigned 64 bit integer vectors. One further development of the package is to facilitate reading 64 bit integer data from csv, etc ... files. I have this function that wraps a call to read.csv to: - read the "int64"

I generated a PDF output file of 10 plots. When I try to view it with Adobe reader (R4 & R5), it will lockup the reader (it is consuming 100% of the CPU) after presenting the 4th plot. I can generate the plots just fine in Windows and as a postscript file reading it with GSview. Is there anyway to tell what might be wrong with the PDF output? The file is 890KB in size if anyone would like

Jeff, Thank you for your reply. The intent was to construct a minimum reproducible example. The same warning occurs when the 'file' argument points to a file on disk with a million lines. But you are correct, my example was slightly malformed and in fact gives an error under R version 3.2.2. Please allow me to try again; in older versions of R, ?? > read.table(file =

I have been using SPLUS on UNIX to do performance analysis of our computers and have some matrices that are about 15M rows with 8 columns. These are 'integers' and therefore take up about 500M of memory. I run on a system with 2G of memory and will utilize over a 1G when processing this data. I am considering using R and was wondering how large addresses spaces are handled under

Hi, is there are reason for not supporting NULL or "NULL" values for argument colClasses in read.table(), much like you can use NULL values for argument 'what' in scan()? This would help quite a bit when reading large data files where only a few columns are of interest. I've modfied read.table() to so it calls scan(what=...) also with NULLs for the fields to be skipped.

Hi all, First off, it is surprising that there are no examples of how to use read.table() under ?read.table ! I am trying to read in a flat file of type 'raw'. It has 1000 rows and 600K columns. I have the RAM to accomplish this, but can't get the data into R using read.table: x <- read.table("data",header=TRUE,colClasses=rep(,600000)) #returns error: no method or

Hi! It seems that read.table() in R 3.0.1 (Linux 64-bit) does not consider quoted integers as an acceptable value for columns for which colClasses="integer". But when colClasses is omitted, these columns are read as integer anyway. For example, let's consider a file named file.dat, containing: "1" "2" > read.table("file.dat",

Hello I noticed that starting with R version 3.3.0 onward, this generates a warning: ?? > txt <- c("a", "3.14") ?? > read.table(file = textConnection(txt), header = FALSE, colClasses = c(x = "character", y = "numeric")) the warning is "not all columns named in 'colClasses' exist" and I guess the change was made in response

You are constructing the equivalent of a two-line data file, and complaining that it is not treating it like it was one line. If it did used to accept this silently [skeptical] then I for one am glad it produces a warning now. -- Sent from my phone. Please excuse my brevity. On October 23, 2017 2:53:21 PM PDT, Benjamin Tyner <btyner at gmail.com> wrote: >Hello > >I noticed that

I am using Version 1.3.0 (2001-06-22) on Windows/2000. Had loaded the 'lattice' and 'grid' libraries and was trying the example on densityplot: data(singer) densityplot( ~ height | voice.part, data = singer, layout = c(2, 4), xlab = "Height (inches)", bw = 5) ## Using a predefined panel function to fit a normal distribution

Hi, I am reading a "|" delimited text file into R using read.table(). I am using colClasses= to specify some variables as factors. Some of these variables include missing values coded as "NA". Unfortunately the R code I am using (pasted bellow) includes "NA" as one of the factor levels. Is it possible to remove the "NA" level from a factor with in

I'm sure this has gotten some attention before, but I have two CSV files generated from vmstat and free that are roughly 6-8 Mb (about 80,000 lines) each. When I try to use read.csv(), R allocates all available memory (about 4.9 Gb) when loading the files, which is over 300 times the size of the raw data. Here are the scripts used to generate the CSV files as well as the R code: Scripts (run

Hello, I have a function for reading a data-frame from a file, which contains E = read.table(file = filename, header = T, colClasses = c(rep("integer",6),"numeric","integer",rep("numeric",8)), ...) Now a small variation arose, where colClasses =

Currently read.table is rather limited in its type conversion. The algorithm is 0) Read as character 1) Try to convert to numeric. If that works, quit 2) Convert to factor unless !as.is. I am thinking about adding more flexibility and more classes by the following two changes. A) Anticipating the arrival of classes for all R objects, add an argument say `colClasses' that allows the user to

I was trying to read in a file and delete lines that did not have the correct number of fields on them. I was reading the file as one character vector per line using 'scan' with sep='\n'. I was then using 'count.fields' with 'textConnection' to the object I just read in. I thought at first the system was locked up, but further testing showed that the