如果前一列包含值，则有条件地填充列？
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【中文标题】如果前一列包含值，则有条件地填充列？【英文标题】：Fill column conditionally if previous column contained value? 【发布时间】：2019-09-15 05:58:00 【问题描述】：我想使用 dplyr::mutate 有条件地填充一列。新变量的一个级别应该对应于上一列中是否存在值，而另一个级别是“其他”条件。
我有一个数据框：
group piece answer agreement
group1 A noise good
group1 A silence good
group1 A silence good
group1 B silence bad
group1 B loud_noise bad
group1 B noise bad
group1 B loud_noise bad
group1 B noise bad
group2 C silence good
group2 C silence good
我想创建一个按组分组的新变量，如果 'bad' 出现在 'agreement' 中，那么值应该是 'inconsistent' 但如果 'agreement' 的所有值都是 'good'，那么值应该是“一致的”。
group piece answer agreement new_agreement
group1 A noise good bad
group1 A silence good bad
group1 A silence good bad
group1 B silence bad bad
group1 B loud_noise bad bad
group1 B noise bad bad
group1 B loud_noise bad bad
group1 B noise bad bad
group2 C silence good good
group2 C silence good good
但 case_when 并没有完全做到这一点 - 它只是再次复制相同的变量：
newdf <- df %>%
group_by(group) %>%
mutate(new_agreement = case_when(agreement == 'bad' ~
"inconsistent", agreement =='good' ~ "consistent")) %>%
as.data.frame()
【问题讨论】：
您的新列与您的问题描述不符。你能编辑一下这个问题吗？ 【参考方案1】：只需添加any(agreement == 'bad')
df %>%
group_by(group) %>%
mutate(new_agreement = case_when(any(agreement == 'bad') ~"inconsistent",
agreement =='good' ~ "consistent"))
# A tibble: 10 x 5
# Groups: group [2]
group piece answer agreement new_agreement
<fct> <fct> <fct> <fct> <chr>
1 group1 A noise good inconsistent
2 group1 A silence good inconsistent
3 group1 A silence good inconsistent
4 group1 B silence bad inconsistent
5 group1 B loud_noise bad inconsistent
6 group1 B noise bad inconsistent
7 group1 B loud_noise bad inconsistent
8 group1 B noise bad inconsistent
9 group2 C silence good consistent
10 group2 C silence good consistent
您甚至可以将if_else 与any 一起使用：
df %>%
group_by(group) %>%
mutate(new_agreement= if_else(any(agreement=="bad"), "inconsistent", "consistent") )
【讨论】：
太棒了，我不知道“任何” - 这是一个非常快速的解决方案。谢谢！【参考方案2】：使用case_when，使用any。
library(dplyr)
df %>%
group_by(group) %>%
mutate(new_agreement = case_when(
any(agreement == 'bad') ~ 'inconsistent',
TRUE ~ 'consistent'))
## A tibble: 10 x 5
## Groups: group [2]
# group piece answer agreement new_agreement
# <fct> <fct> <fct> <fct> <chr>
# 1 group1 A noise good inconsistent
# 2 group1 A silence good inconsistent
# 3 group1 A silence good inconsistent
# 4 group1 B silence bad inconsistent
# 5 group1 B loud_noise bad inconsistent
# 6 group1 B noise bad inconsistent
# 7 group1 B loud_noise bad inconsistent
# 8 group1 B noise bad inconsistent
# 9 group2 C silence good consistent
#10 group2 C silence good consistent
dput 格式的数据。
df <-
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L), .Label = c("group1", "group2"),
class = "factor"), piece = structure(c(1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 3L, 3L), .Label = c("A", "B", "C"),
class = "factor"), answer = structure(c(2L, 3L, 3L,
3L, 1L, 2L, 1L, 2L, 3L, 3L), .Label = c("loud_noise",
"noise", "silence"), class = "factor"), agreement =
structure(c(2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L),
.Label = c("bad", "good"), class = "factor")),
class = "data.frame", row.names = c(NA, -10L))
【讨论】：
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