我想在R中使用交叉表dplyr
.我有充分的理由不仅使用base table()
命令.
table(mtcars$cyl, mtcars$gear)
3 4 5
4 1 8 2
6 2 4 1
8 12 0 2
library(dplyr)
library(tidyr)
mtcars %>%
group_by(cyl, gear) %>%
tally() %>%
spread(gear, n, fill = 0)
Source: local data frame [3 x 4]
cyl 3 4 5
1 4 1 8 2
2 6 2 4 1
3 8 12 0 2
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这一切都很好.但是当group_by()
变量中缺少值时,它似乎就会崩溃.
mtcars %>%
mutate(
cyl = ifelse(cyl > 6, NA, cyl),
gear = ifelse(gear > 4, NA, gear)
) %>%
group_by(cyl, gear) %>%
tally()
Source: local data frame [8 x 3]
Groups: cyl
cyl gear n
1 4 3 1
2 4 4 8
3 4 NA 2
4 6 3 2
5 6 4 4
6 6 NA 1
7 NA 3 12
8 NA NA 2
# DITTO # %>%
spread(gear, n)
Error in if (any(names2(x) == "")) { :
missing value where TRUE/FALSE needed
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我想我想要的是NA
像你这样的专栏table(..., useNA = "always")
.有小费吗?
一种选择是NA
用标签替换s.这可以通过以下方式轻松完成mutate_each
:
mtcars %>%
mutate(
cyl = ifelse(cyl > 6, NA, cyl),
gear = ifelse(gear > 4, NA, gear)
) %>%
group_by(cyl, gear) %>%
tally() %>%
ungroup() %>%
mutate_each(funs(replace(., is.na(.), 'missing'))) %>%
spread(gear, n)
# cyl 3 4 missing
# 1 4 1 8 2
# 2 6 2 4 1
# 3 missing 12 NA 2
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