我试图通过每行中非 NA 的计数在 dplyr 中总结(/突变)......不断给出错误的答案。
像布尔值一样的算术sum(FALSE + TRUE + FALSE + TRUE + TRUE)
确实加起来是 3,那么问题出在哪里?为什么 dplyr 没有捕捉到错误?
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
通过使用格雷码进行调试,我看到!is.na()
除了 Field1 之外的所有 s 都表现得很奇怪:
mutate(na_count = sum(16*!is.na(Field1) + 8*!is.na(Field2) + 4*!is.na(Field3) + 2*!is.na(Field4) + !is.na(Field5)))
只给出 16 或 0