similar to: R's IO speed

Dear List, I frequently use the data() function to load csv files (with separator ";") into R session, typically data(myfile) loads myfile.csv from my working/data directory into R. Now, in 1.4.0 version, everything works as expected, but with one difference: The values readed in older versions in "num" mode are now readed as "int" mode, converting the values

Hello everyone, I'm writting a little script that will read a matrix from a file i.e. 0,.11,.22,.4 .11,0,.5,.3 .22,.5,0,.7 anb so on and will then calculate some standard stats for nets (i.e. centralization, degree, etc). So far I have opened the file and read the contents, however I' m using readLines(filename) to read the file and it returns it as

I am using an example posted in this help forum to work with a file. the head of the file looks like: 988887 2007-03-05 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 0 0 988887 2007-03-06 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 1 0 988887 2007-03-07 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100 2 0 988887 2007-03-08 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100

I've spent some time trying to wrap my head around reading in large csv files with the ff-package. I think I know how to do it, but am bumping into some problems. I've tried to recreate the issues as best as I can with a smaller example and maybe someone can help explain the problems. The following code just creates a csv file with an integer column, character column and logical column.

Hi, The colClasses seem to be supressing 'NA' vlaues. How do I fix this? R script and first 5 lines of output is below. File "test2.dat" has blanks that are read as "NA" when I do not use 'colClasses', but as blanks when I use 'colClasses'. temp.df <- read.fwf("test2.dat", width=c(10,1,1,1,1,2,2,3,3,1),

Hi all. I'm reading in a flat, comma-delimited flat file using read.csv. It works marvelously for the most part. I am using the colClasses argument to, basically, create numeric, factor and character classes for the columns I'm reading in. However, a couple of the fields in the file are date fields. I'm fully aware that POSIXct can be used as a class, however the field must obey,

I have a .txt file obtained by saving a data frame in which the first four columns are factors (but represented as 1,2,3 etc). The first four lines are "Pig" "Evit" "Cu" "Litter" "Start" "Weight" "Feed" "Time" "4601" "1" "1" "1" 26.5 26.5 NA 1 "4601" "1"

I am using 'read.csv' in V2.0.1 to read in a CSV file with the colClasses option and am getting an error from 'scan' when it encounters a non-numeric value for a 'numeric' column, i.e. > ds <- read.csv(in_file, nrows=irow, row.names=NULL, colClasses=zclass, comment.char="") Error in scan(file = file, what = what, sep = sep, quote =

*Dear R users, Ive just started using the ff package. There is a csv file (~4Gb) with 7 columns and 6e+7 rows. I want to read only column from the file, skipping the first 100 rows. Below Ive provided different outcomes, which will clarify my problem * > sessionInfo() R version 2.14.2 (2012-02-29) Platform: x86_64-pc-mingw32/x64 (64-bit) locale: ... attached base packages: [1] tools

Full_Name: Shigeru Mase Version: 2.0.1 OS: Linux (Debian) Submission from: (NULL) (222.149.162.192) help.search("Mem") shows there is an object "Memory-limits" in the base package. But commads "Memory-limits", or "Memory-limits()", causes an error message: Error: Object "Memory" not found. In addition, help(Memory-limits) displays the document

I have been trying to read in a large data set using read.table, but I've only been able to grab the first 50,871 rows of the total 122,269 rows. > f <- read.table("http://www.cs.odu.edu/~fmccown/R/Tchange_rates_crawled.dat", header=TRUE, nrows=123000, comment.char="", sep="\t") > length(f$change_rate) [1] 50871 From searching the email archives,

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",

>>>>> "KevinW" == Kevin Wright <kwright68 at gmail.com> >>>>> on Mon, 21 Nov 2005 18:13:36 +0100 (CET) writes: KevinW> Full_Name: Kevin Wright KevinW> Version: 2.2.0 KevinW> OS: Windows 2000 ^^^^^^^ this must be part of the problem KevinW> Submission from: (NULL) (170.54.58.4) KevinW> Apologies if

Hi all, I've simple code to read a file (verify.txt in the same directory as the script file) but when I run this I get "Error in eval(expr, envir, enclos) : object "y" not found". data_model.df = read.table("./verify.txt", header=TRUE, nrows=10); f <- lm(y ~ x) Could someone pls tell me what's wrong with this code? Sincere thanks!

If read.csv's colClasses= argument is NOT used then read.csv accepts double quoted numerics: 1: > read.csv(stdin()) 0: A,B 1: "1",1 2: "2",2 3: A B 1 1 1 2 2 2 However, if colClasses is used then it seems that it does not: > read.csv(stdin(), colClasses = "numeric") 0: A,B 1: "1",1 2: "2",2 3: Error in scan(file, what, nmax, sep,

How do I manipulate the read.table function to read in only the 2nd column??? [[alternative HTML version deleted]]

Buenas Tardes, Les escribo para solicitarles una ayuda dado que tengo 2 tablas, una con los campos: cedula | nombre | direccion y la otra con la tabla: cedula | barrio | municipio Lo que necesito es hacer una comparación del campo cedula de las dos tablas y si son iguales, agregarle los campos barrio y municipio de la segunda tabla a la fila correspondiente de esa cedula de la primera

Dear all: I have two larges files with 2000 columns. For each file I am performing a loop to extract the "i"th element of each file and create a data frame with both "i"th elements in order to perform further analysis. I am not extracting all the "i"th elements but only certain which I am indicating on a vector called "d". See an example of my code below

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

Hallo, I would like to use to read.xls function from the gdata package to read data from Microsoft Excel files but I experienced a problem: For example I used the following code: testfile<-read.xls("/home/.../wsjecon0603.xls", #file path header=F, dec=",", na.strings="n.a.", skip=5, sheet=2,