我想创建一个计数变量,其中每个给定年份的Z == 0的人数。如下图所示:
PersonID Year Z Count*
1 1990 0 1
2 1990 1 1
3 1990 1 1
4 1990 2 1
5 1990 1 1
1 1991 1 3
2 1991 0 3
3 1991 1 3
4 1991 0 3
5 1991 0 3
1 1992 NA 1
2 1992 2 1
3 1992 2 1
4 1992 0 1
5 1993 1 0
1 1993 1 0
2 1993 2 0
3 1993 NA 0
4 1993 1 0
5 1994 0 5
1 1994 0 5
2 1994 0 5
3 1994 0 5
4 1994 0 5
我看了之前的R-scripts并发现了这个
library(dplyr)
sum_data <- data %>% group_by(PersonID) %>% summarise(Count = sum(Z, na.rm=T))
有人可以帮助我做到这一点吗? count变量基本上应该计算Z == 0的总人数,格式与我上面说明的相同。谢谢!
dput(data)
structure(list(PersonID = c(1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L),
Year = c(1990L, 1990L, 1990L, 1990L, 1990L, 1991L, 1991L,
1991L, 1991L, 1991L, 1992L, 1992L, 1992L, 1992L, 1993L, 1993L,
1993L, 1993L, 1993L, 1994L, 1994L, 1994L, 1994L, 1994L),
Z = c(0L, 1L, 1L, 2L, 1L, 1L, 0L, 1L, 0L, 0L, NA, 2L, 2L,
0L, 1L, 1L, 2L, NA, 1L, 0L, 0L, 0L, 0L, 0L)), .Names = c("PersonID",
"Year", "Z"), class = "data.frame", row.names = c(NA, -24L))
答案 0 :(得分:1)
这是一个简单的解决方案:
library(dplyr)
sum_data <- df %>%
mutate(Z=replace(Z, is.na(Z), 1)) %>%
mutate(temp = ifelse(Z == 0, 1, 0)) %>%
group_by(Year) %>%
summarize(count = sum(temp))
基本上这就是代码正在做的事情:
mutate(Z=replace(Z, is.na(Z), 1))
将NA替换为1(可选)mutate(temp = ifelse(Z == 0, 1, 0))
创建条件临时值
变量:ifelse(Z == 0, 1, 0)
说如果Z == 0则值为1
否则0 group_by(Year)
非常详尽:)它将数据框分组
年summarize(count = sum(temp))
创建一个count变量
早期生成的temp的总和结果:
Year count
<int> <int>
1 1990 5
2 1991 5
3 1992 4
4 1993 5
5 1994 5
如果您想将此数据加入原始数据框,只需使用join:
left_join(df, sum_data)
Joining, by = "Year"
PersonID Year Z count
1 1 1990 0 1
2 2 1990 1 1
3 3 1990 1 1
4 4 1990 2 1
5 5 1990 1 1
6 1 1991 1 3
7 2 1991 0 3
8 3 1991 1 3
9 4 1991 0 3
10 5 1991 0 3
11 1 1992 NA 1
12 2 1992 2 1
13 3 1992 2 1
14 4 1992 0 1
15 5 1993 1 0
16 1 1993 1 0
17 2 1993 2 0
18 3 1993 NA 0
19 4 1993 1 0
20 5 1994 0 5
21 1 1994 0 5
22 2 1994 0 5
23 3 1994 0 5
24 4 1994 0 5
答案 1 :(得分:1)
试试这个:
library(dplyr)
df <- left_join(data, data %>% filter(Z==0) %>% group_by(Year) %>% summarise(Count = n()))
df[is.na(df$Count),]$Count <- 0
PersonID Year Z Count
1 1 1990 0 1
2 2 1990 1 1
3 3 1990 1 1
4 4 1990 2 1
5 5 1990 1 1
6 1 1991 1 3
7 2 1991 0 3
8 3 1991 1 3
9 4 1991 0 3
10 5 1991 0 3
11 1 1992 NA 1
12 2 1992 2 1
13 3 1992 2 1
14 4 1992 0 1
15 5 1993 1 0
16 1 1993 1 0
17 2 1993 2 0
18 3 1993 NA 0
19 4 1993 1 0
20 5 1994 0 5
21 1 1994 0 5
22 2 1994 0 5
23 3 1994 0 5
24 4 1994 0 5