On Jun 14, 2010, at 4:45 PM, Douglas M. Hultstrand wrote:

Hello,

I currently splitting a file into individual files (time series each separated into one file), the file I read in skips the first four lines and extracts the data columns I need. I was wondering if there is a way for R to automatically scan and separate the files based on the head information?

The header delineates the observation with a 254 space time space day space month space year.
254      0     26      NOV    1995

I would like to then use the program I have written to do the analysis. I have attached a small subset text file of data (two observations). Any thoughts would be very helpful.

# Read in data file
data <- read.table("file.txt", skip=4, header=F)
temp <- data$V4
elev <- data$V3

Yes:

> ctxt <- textConnection("\n\n\n\n254 0 26 NOV 1995\n \n\n") # simulating a file with four lines to be skipped and a fifth line to be read
>> dat <- read.table(file=ctxt, skip=4, header=F, nrows=1)
> str(dat)
'data.frame':   1 obs. of  5 variables:
 $ V1: int 254
 $ V2: int 0
 $ V3: int 26
 $ V4: Factor w/ 1 level "NOV": 1
 $ V5: int 1995

If you wanted the months to be character variables then use as.is=TRUE or stringsAsFactors=FALSE to control the default creation of factors.



Thank you,
Doug

--
---------------------------------
Douglas M. Hultstrand, MS
Senior Hydrometeorologist
Metstat, Inc. Windsor, Colorado
voice: 720.771.5840
email: dmhul...@metstat.com
web: http://www.metstat.com
---------------------------------

   254      0     26      NOV    1995
     1  24232  72694  44.92N123.02W    61   2302
     2    100   1960   2680    149  99999      4
     3           SLE                99999     kt
     9  10071     61    106     94    180     10
     5  10037     89    110     82    183     12
     4  10000    120    106     84    186     12
     6   9780    304  99999  99999    205     19
     6   9500    544     74     59    221     19
   254     12     26      NOV    1995
     1  24232  72694  44.92N123.02W    61   2302
     2    100   1960   2680    149  99999      4
     3           SLE                99999     kt
     9  10071     61    106     94    180     10
     5  10037     89    110     82    183     12
     4  10000    120    106     84    186     12
     6   9780    304  99999  99999    205     19
     6   9500    544     74     59    221     19
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