On Tue, 7 Feb 2012, David Winsemius wrote:
On Feb 7, 2012, at 12:56 PM, Jeff Newmiller wrote:
On Tue, 7 Feb 2012, Alexander Shenkin wrote:
Hello Folks,
I'm trying to vectorize a loop that processes rows of a dataframe. It
involves lots of conditionals, such as "If column 10 == 3, and if column
3 is True, and both column 5 and 6 are False, then set column 4 to True".
So, for example, any ideas about vectorizing the following?
df = data.frame( list(a=c(1,2,3,4), b=c("a","b","c","d"), c=c(T,F,T,F),
d=NA, e=c(F,F,T,T)) )
for (i in 1:nrow(df)) {
if (df[i,3] %in% c(FALSE,NA) & (df[i,1] > 2 | df[i,5]) ) {
df[i,4] = 1
}
if (df[i,5] %in% c(TRUE, NA) & df[i,2] == "b") {
df[i,4] = 2
df[i,5] = T
}
}
Your code attempts to do some things with NA that won't behave the way
you expect them to. Specifically, you cannot use %in% to test for NA,
Huh?
NA %in% NA
[1] TRUE
NA %in% c(5, NA)
[1] TRUE
NA %in% c(5, 6)
[1] FALSE
Sorry, SQL rules bleeding through... %in% is clearly more forgiving in R
than IN is in SQL. However, the second if did check whether df[i,5] was
NA, yet the first if did not. Since comparisons with NA are neither false
nor true that test failed.
NA | 1
[1] TRUE
NA & 1
[1] NA
NA > 1
[1] NA
# intermediate logical vectors for clarity
tmp <- ( is.na(df[[3]]) | !df[[3]] ) & ( df[[1]] > 2 | df[[5]] )
tmp2 <- ( is.na(df[[5]]) | df[[5]] ) & df[[2]] == "b"
df[ tmp, "d" ] <- 1
df[ tmp2, "d" ] <- 2
df[ tmp2, "e" ] <- TRUE
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...
DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go...
Live: OO#.. Dead: OO#.. Playing
Research Engineer (Solar/Batteries O.O#. #.O#. with
/Software/Embedded Controllers) .OO#. .OO#. rocks...1k
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
