[R] Vectorizing a loop

[Alexander Shenkin]

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
}

}

Thanks,
Allie

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[Jeff Newmiller]

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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[Petr Savicky]

On Tue, Feb 07, 2012 at 11:39:42AM -0500, 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
> }
>
> }

Hi.

Try the following.

cond1 <- (df[,3] %in% c(FALSE,NA)) & (df[,1] > 2 | df[,5])
df[,4] <- ifelse(cond1, 1, df[,4])
cond2 <- (df[,5] %in% c(TRUE, NA)) & (df[,2] == "b")
df[,4] <- ifelse(cond2, 2, df[,4])
df[,5] <- ifelse(cond2, TRUE, df[,5])

Hope this helps.

Petr Savicky.

[David Winsemius]

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

--
David.

David Winsemius, MD
West Hartford, CT

[Jeff Newmiller]

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