This is the same set of data that I have been working with for those
in the know. it is a matrix of ~174 columns and ~70,000 rows. I have
it as a zoo object, but I could read it in as just a matrix as long as
the date time stamp won't be corrupted.
here is an example of what a column would look like:
1/1/06 12:00, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5,6 ,7, NA
#read in with the following thanks to Gabor
# chron
library(chron)
fmt.chron <- function(x) {
+ chron(sub(" .*", "", x), gsub(".* (.*)", "\\1:00", x))
+ }
z1 <- read.zoo("all.csv", sep = ",", header = TRUE, FUN = fmt.chron)
#this part works just fine and I can plot and analyze data till my
hearts content
I need to replace NA (~700,000+) with the numeric value 9999 for a
beam forming exercise that we are conducting with a geophysicist in
matlab. I can't get it into excel in the present form because it is
too big. I was wondering if there was an easy way to do such a thing
in R?
I tried the following:
dat <- sapply(z1, function(x) {x[is.na(x)] <- 9999; x})
and I got the following error:
Error in array(unlist(answer, recursive = FALSE), dim = c(common.len, :
'dim' specifies too large an array
thanks for the help
Stephen
--
Let's not spend our time and resources thinking about things that are
so little or so large that all they really do for us is puff us up and
make us feel like gods. We are mammals, and have not exhausted the
annoying little problems of being mammals.
-K. Mullis