dplyr错误:组合group_by,mutate和ifelse时的奇怪问题。这是一个错误吗?

时间:2015-03-24 03:50:46

标签: r dplyr

我在dplyr以及group_by,mutate和ifelse的组合方面遇到了奇怪的问题。请考虑以下data.frame

> df1
  crawl.id group.id hits.diff
1        1        1        NA
2        1        2        NA
3        2        2         0
4        1        3        NA
5        1        3        NA
6        1        3        NA

当我使用以下代码时

library(dplyr)
df1 %>%
  group_by(group.id) %>% 
  mutate( hits.consumed = ifelse(hits.diff<=0,-hits.diff,0) )

出于某种原因,我得到了

Error: incompatible types, expecting a logical vector**

但是,删除group_by()ifelse一切都按预期工作:

df1 %>%
  mutate( hits.consumed = ifelse(hits.diff<=0,-hits.diff,0) )

crawl.id group.id hits.diff hits.consumed
1        1        1        NA            NA
2        1        2        NA            NA
3        2        2         0             0
4        1        3        NA            NA
5        1        3        NA            NA
6        1        3        NA            NA

df1 %>%
  group_by( group.id ) %>%
  mutate( hits.consumed = -hits.diff )

  crawl.id group.id hits.diff hits.consumed
1        1        1        NA            NA
2        1        2        NA            NA
3        2        2         0             0
4        1        3        NA            NA
5        1        3        NA            NA
6        1        3        NA            NA

是错误还是功能?任何人都可以复制这个吗? 关于group_by,mutate和ifelse的特定组合使它失败的特别之处是什么?

我自己的研究使我在这里: https://github.com/hadley/dplyr/issues/464 这表明现在应该修复它。

以下是dput(df1)

structure(list(crawl.id = c(1, 1, 2, 1, 1, 1), group.id = structure(c(1L, 
2L, 2L, 3L, 3L, 3L), .Label = c("1", "2", "3"), class = "factor"), 
    hits.diff = c(NA, NA, 0, NA, NA, NA)), .Names = c("crawl.id", 
"group.id", "hits.diff"), row.names = c(NA, -6L), class = "data.frame")

1 个答案:

答案 0 :(得分:33)

将所有内容全部包含在as.numeric中以强制输出格式,因此NA s(默认为logical)不会覆盖输出变量的类:

df1 %>%
  group_by(group.id) %>% 
  mutate( hits.consumed = as.numeric(ifelse(hits.diff<=0,-hits.diff,0)) )

#  crawl.id group.id hits.diff hits.consumed
#1        1        1        NA            NA
#2        1        2        NA            NA
#3        2        2         0             0
#4        1        3        NA            NA
#5        1        3        NA            NA
#6        1        3        NA            NA

非常确定这与此处的问题相同:Custom sum function in dplyr returns inconsistent results,因为此结果表明:

out <- df1[1:2,] %>%  mutate( hits.consumed = ifelse(hits.diff <= 0, -hits.diff, 0))
class(out$hits.consumed)
#[1] "logical"
out <- df1[1:3,] %>%  mutate( hits.consumed = ifelse(hits.diff <= 0, -hits.diff, 0))
class(out$hits.consumed)
#[1] "numeric"