Or maybe it's better to coerce Temp and Press to numeric, if they are
variables temperature and presssure.
dat$Time <- as.Date(dat$Time, format="%m/%d/%Y")
dat$Temp <- as.numeric(dat$Temp)
dat$Press <- as.numeric(dat$Press)
This makes those '#N/A' values NA.
Rui Barradas
Em 10-07-2012 09:34, Rui Barradas escreveu:
Hello,
My approach was slightly different, to use readLines to take care of the
header and read.table for the data. This works with the new dataset
you've posted, but we must use the option comment.char = "".
Try the following.
head <- readLines("test.txt", n=4)[4]
dat <- read.table("test.txt", skip=5, sep=";", stringsAsFactors=FALSE,
comment.char="c")
names(dat) <- unlist(strsplit(head, ";"))
dat$Time <- as.Date(dat$Time, format="%m/%d/%Y")
dat$Temp[dat$Temp == '#N/A'] <- NA
dat$Press[dat$Press == '#N/A'] <- NA
dat
It works with me, good luck.
Rui Barradas
Em 10-07-2012 06:41, vioravis escreveu:
Thanks a lot Rui and Arun.
The methods work fine with the data I gave but when I tried the two
methods
with the following semi-colon separated data using sep = ";". Only the
first
3 columnns are read properly rest of the columns are either empty or NAs.
**********************************************************************************************
Remove this line
Remove this line
Remove this line
Time;Actual Speed;Actual Direction;Temp;Press;Value1;Value2
;[m/s];[°];°C;[hPa];[MWh];[MWh]
1/1/2012;0.0;0;#N/A;#N/A;0.0000;0.0000
1/2/2012;0.0;0;#N/A;#N/A;0.0000;0.0000
1/3/2012;0.0;0;#N/A;#N/A;1.5651;2.2112
1/4/2012;0.0;0;#N/A;#N/A;1.0000;2.0000
1/5/2012;0.0;0;#N/A;#N/A;3.2578;7.5455
***********************************************************************************************
I used the following code:
dat1<-read.table("testInput.txt",sep=";",skip=3,fill=TRUE,header=TRUE)
dat1<-dat1[-1,]
row.names(dat1)<-1:nrow(dat1)
Could you please let me know what is wrong with this approach?
Thank you.
Ravi
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