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,
and you cannot give the "if" function an NA. It only appears to work
because you don't actually give it a complete set of test values
consistent with your tests in the loop. My guess at your intent is:
df <- data.frame( list( a=c(1,2,3,4,5)
, b=c("a","b","c","d","e")
, c=c(TRUE,FALSE,TRUE,FALSE,NA)
, d=NA
, e=c(FALSE,FALSE,TRUE,TRUE,NA)
) )
tmpdf <- df
for (i in 1:nrow(df)) {
if ( ( is.na(df[i,3]) || !df[i,3] ) && ( df[i,1] > 2 || ( is.na(
df[i,5] ) || df[i,5] ) ) ) {
df[i,4] <- 1
}
if ( ( is.na( df[i,5] ) || df[i,5] ) && df[i,2] == "b" ) {
df[i,4] <- 2
df[i,5] <- TRUE
}
}
df2 <- df
df <- tmpdf
# 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
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