summarize/mutate get operator precedence of + over ! wrong

[smcinerney]

summarize/mutate gets the precedence of + over ! wrong

WRONG: summarize(nna_count = sum(!is.na(Field1) + !is.na(Field2) + !is.na(Field3) + !is.na(Field4) + !is.na(Field5)))

# WORKAROUND1: override precedence of +,!
df %.% group_by(id,date) %.%
 mutate(nna_count =
   (!is.na(Field1)) + (!is.na(Field2)) + (!is.na(Field3)) + (!is.na(Field4)) + (!is.na(Field5)) 
 ) 

# WORKAROUND2: pass one single vectorized expression
df %.% regroup(list(quote(id),quote(date))) %.%
+   summarize(nna_count = sum(!is.na(c(Field1,Field2,Field3,Field4,Field5))))

---

I'm trying to summarize(/mutate) in dplyr by the count of non-NAs in each row... keeps giving wrong answer.

Arithmetic on booleans like sum(FALSE + TRUE + FALSE + TRUE + TRUE) does indeed add up to 3, so where is the problem? And why does dplyr not catch the error?

N = 9
set.seed(1234)
df <- data.frame(id=c(1,1,1,2,2,2,3,3,3), date=c('2005','2006','2007'),
                 Field1 = ifelse(runif(N)>.5, runif(N, 5,30), NA),
                 Field2 = ifelse(runif(N)>.5, runif(N, 4,22), NA),
                 Field3 = ifelse(runif(N)>.5, runif(N, 7,18), NA),
                 Field4 = ifelse(runif(N)>.5, runif(N, 9,25), NA),
                 Field5 = ifelse(runif(N)>.5, runif(N, 3,30), NA) )

# > df
# id date   Field1    Field2    Field3    Field4    Field5
#1  1 2005       NA        NA        NA        NA        NA
#2  1 2006 22.33978        NA        NA 12.824412  6.850614
#3  1 2007 18.62437        NA 12.334904        NA        NA
#4  2 2005 12.06834        NA  9.683217 13.929516  8.296716
#5  2 2006 28.08584        NA 15.420058        NA        NA
#6  2 2007 12.30790        NA  7.811579  9.826346        NA
#7  3 2005       NA        NA        NA 18.033117        NA
#8  3 2006       NA  7.259732 14.889989        NA  7.320774
#9  3 2007 11.67052 17.674071        NA        NA 27.197018


# Trying to summarize by the count of non-NAs in each row...!
df %.% regroup(list(quote(id),quote(date))) %.%
    summarize(nna_count = sum(!is.na(Field1) + !is.na(Field2) + !is.na(Field3) + !is.na(Field4) + !is.na(Field5)))

# TOTALLY WRONG?!

# Source: local data frame [9 x 3]
# Groups: id
# 
# id date nna_count
#1  1 2005        0
#2  1 2006        1
#3  1 2007        1
#4  2 2005        1
#5  2 2006        1
#6  2 2007        1
#7  3 2005        0
#8  3 2006        0
#9  3 2007        0

By debugging with a Gray-code, I see all the !is.na()s acting weird except for Field1:

mutate(na_count = sum(16*!is.na(Field1) + 8*!is.na(Field2) + 4*!is.na(Field3) + 2*!is.na(Field4) + !is.na(Field5))) 

only ever gives 16 or 0

[smcinerney]

Apparently this is a generic R bug, not dplyr:
http://stackoverflow.com/questions/17651687/behavior-of-summing-is-na-results