由于NA的原因，无法对数据帧进行子集(过滤) [英] Unable to subset (filter) a data frame due to NA's

问题描述

为什么在dplyr的 filter 下面的代码中没有返回与base R子设置相同的data.frame?

Why in the code below dplyr's filter doesn't return the same data.frame as base R subsetting?

实际上，它们都不符合预期.我想删除同时 b == 1和c == 1 的观察/行.也就是说，我只想删除第三行.

In fact none of them works as expected. I'd like to remove observations/rows which, simultaneously, b==1 AND c==1. That is, I'd like to remove only the third row.

require(dplyr)
df <- data.frame(a=c(0,0,0,0,1,1,1),
  b=c(0,0,1,1,0,0,1),
  c=c(1,NA,1,NA,1,NA,NA))

filter(df, !(b==1 & c==1))

df[!(df$b==1 & df$c==1),]

推荐答案

或使用 complete.cases 将 NA 转换为 FALSE 结果逻辑向量，以便您可以在取反后选择相应的行，这利用了 NA&F = F :

Or use complete.cases to convert NA to FALSE in the result logic vector so that you can pick the corresponding rows up after the negation, and this uses the fact that NA & F = F:

filter(df, !(b == 1 & c == 1 & complete.cases(df[c('b', 'c')])))

#   a b  c
# 1 0 0  1
# 2 0 0 NA
# 3 0 1 NA
# 4 1 0  1
# 5 1 0 NA
# 6 1 1 NA

这里涉及到更多带有 NA 的逻辑运算，乍一看有点令人困惑，但它们遵循逻辑:

More logical operations with NA involved here, which is a little bit confusing at the first glance but they are following the logic:

NA & F
# [1] FALSE
NA | T
# [1] TRUE
NA & T
# [1] NA
NA | F
# [1] NA

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