[英]Generate new column in dataframe, based on group-event in nested groups
I have a dataframe with three "main"-groups (x: 1, 2, 3), three groups within the main-groups (v: 2, 3 or 1) and some events within the main-groups (0 and 1 in y): 我有一个数据框,其中包含三个“主要”组(x:1、2、3),三个主要组(v:2、3或1)和主要组中的一些事件(0和1 Y):
x <- c(1, 1, 1, 2, 2, 3, 3, 3, 3)
v <- c(2, 3, 3, 2, 2, 1, 1, 2, 2)
y <- c(0, 0, 1, 0, 0, 0, 0, 0, 1)
df <- data.frame(x, v, y)
df
> df
x v y
1 1 2 0
2 1 3 0
3 1 3 1
4 2 2 0
5 2 2 0
6 3 1 0
7 3 1 0
8 3 2 0
9 3 2 1
For example: In group 1 (x = 1) there are two more groups (v = 2 and v = 3), event y = 1 happens in group x = 1 and v = 3. 例如:在组1(x = 1)中,还有另外两个组(v = 2和v = 3),事件y = 1发生在组x = 1和v = 3中。
Now i want to generate a new column z, based on the events in y: if there is any y = 1 in one group, all cases in group v in x should get a 1 for z; 现在,我想基于y中的事件生成一个新的列z:如果一个组中的y = 1,则x中v组中的所有情况都应为z取1; else NA.
不,不。 How can z be generated this way?
如何以这种方式生成z? df should look like:
df应该看起来像:
> df
x v y z
1 1 2 0 NA
2 1 3 0 1
3 1 3 1 1
4 2 2 0 NA
5 2 2 0 NA
6 3 1 0 1
7 3 1 1 1
8 3 2 0 NA
9 3 2 0 NA
I am grateful for any help. 感谢您的帮助。
Try this: 尝试这个:
library(dplyr)
df %>%
group_by(x, v) %>%
mutate(
z = ifelse(any(y == 1), 1, NA)
)
df %>% group_by(x, v) %>% mutate(z = if(any(y == 1)) 1 else NA)
通过分组后x
和y
,新列z
填充有1
',如果有任何小号1
的在y
并与NA
的说明。
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