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I have a commonly recurring problem and wondered if folks would share tips. I routinely get tab-delimited text files that I need to read in. In very many cases, I get: > a <- read.table('junk.txt.txt',header=T,skip=10,sep="\t") Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : line 67 did not have 88 elements I am typically able to go

I am using R2.4.1 calling a text file contains the following data structure: when i call the file into R using tData<-read.table("c:\\test.txt") it gave me Error saying, irregular column in the data set however i need to use the below type of data Is there any alternative in R? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 0010 0028 0061 0088 0010 0042 0084 0004 0010 0055 0010 0018 0040 0042

...t; dates("01/01/2000", format="dd/mm/yyyy") Error in names<-.default(*tmp*, value = fnames) : names attribute must be the same length as the vector In addition: Warning message: wrong number of fields in entry(ies) 1 in: unpaste(dates., sep = fmt$sep, fnames = fmt$periods, nfields = 3) Shall I send a bug report or is this a known problem? Regards -- Dr. Jens Oehlschlägel-Akiyoshi MD FACTORY GmbH Bayerstrasse 21 80335 München Tel.: 089 545 28-27 Fax.: 089 545 28-10 http://www.mdfactory.de Standard Disclaimers: Opinions expressed here are personal and are not otherwis...

...;-.data.frame`(`*tmp*`, "time2", value = list(sec = c(0, 0, : replacement has 9 rows, data has 10 nor trying: > tdata$time2=chron(times=as.character(tdata$time, format= "hh:mm")) In addition: Warning messages: 1: In unpaste(times, sep = fmt$sep, fnames = fmt$periods, nfields = 3) : wrong number of fields in entry(ies) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 2: In convert.times(times., fmt) : NAs introduced by coercion 3: In convert.times(times., fmt) : NAs introduced by coercion 4: In convert.times(times., fmt) : NAs introduced by coercion gives me any valid times from my ti...

...ot;],format=c("y/m/d","h:m:s")) Error in convert.dates(dates., format = format[[1]], origin = origin.) : format y/m/d may be incorrect In addition: Warning messages: 1: 1796 entries set to NA due to wrong number of fields in: unpaste(dates., sep = fmt$sep, fnames = fmt$periods, nfields = 3) 2: NAs introduced by coercion 3: NAs introduced by coercion 4: NAs introduced by coercion Thanks, Joel Allen Institute of Applied Sciences University of North Texas -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuw...

...locations */ /* returned by malloc in ncread */ double ofs, scl; /* offset and scaling factors */ double *ptr; SEXP field, dim, dimnames, lon, lat, tim, missing; printf("ncfile= %s, vname=%s\n",fname,vname); printf("\nfield->%x\nlon -> %x\nlat -> %x\ntim -> %x\nmissing -> %x\n", field,lon,lat,tim,missing); /* Call the function dealing with the netCDF data */ /* The data is placed in memeory */ status=ncread(fname, vname, &nx, &ny, &nt, &ptrs, &scl, &ofs);...

...ows, I get an error: > wet.bnd <- get.bnddata("wetlands\\info", "WETLANDS.BND") Error in get.bnddata("wetlands\\info", "WETLANDS.BND") : Couldn't open table get.tablenames() shows that the table exists TableName InfoFile NFields RecSize NRecords External 1 WETLANDS.BND ARC0000 1 16 1 FALSE 2 WETLANDS.PAT ARC0001 1 26 355 FALSE 3 WETLANDS.TIC and if I use get.tabledata() the table will open (but the values are set to zero) > wet.bnd <-...

...Number of ARCS:16723 Number of CENTROIDS:1625 Number of LABELS:1624 Number of POLYGONS:1625 Number of TOLERANCES:10 > attach(d) > plotpal(arc, pal) > newarc<-thinlines(arc,.05) > plotpal(newarc, pal) > get.tablenames("info/") TableName InfoFile NFields RecSize NRecords External 1 TR13.AAT ARC0001 1 38 16723 TRUE 2 TR13.BND ARC0002 1 32 1 FALSE 3 TR13.PAT ARC0003 1 178 1625 FALSE 4 TR13.TIC AR...

Hi all, I have imported a value 3:00 from Excel into R using read.csv. I want R to recognise it as 3:00am (time data). How do I do it? Thanks in advance, Chris -- View this message in context: http://n4.nabble.com/R-treating-time-tp1008608p1008608.html Sent from the R help mailing list archive at Nabble.com.

When reading comma-delimited files as saved from a spreadsheet (unfortunately many of my scientific collaborators give me these) in read.table(), missing values are spotted most of the time. Unfortunately when comma is the first character on the line it gets it wrong. For example, reading the file 1,,3 ,5,6 ,8,9 with read.table("test.dat", header=F, sep=",") R gives

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