尝试按类别和条件获取总计,但不对数据进行分组。 可复制的示例:
df <- data.frame("class" = c("a","b","c","d","b","b","b","b","c","c","a"),"increment" = c(0,0,0,0,0,0,32,12,0,0,0))
R> df
class increment
1 a 0
2 b 0
3 c 0
4 d 0
5 b 0
6 b 0
7 b 32
8 b 12
9 c 0
10 c 0
11 a 0
我希望所有情况下增量都不同于零,但对于每个班级。
所需的输出:
R> df
class increment increment_count_per_class
1 a 0 0
2 b 0 2
3 c 0 0
4 d 0 0
5 b 0 2
6 b 0 2
7 b 32 2
8 b 12 2
9 c 0 0
10 c 0 0
11 a 0 0
下面是我的第一种方法,但是我知道使用dplyr一定要花些时间:
df <- df %>% mutate(has.increment = ifelse(increment>0,1,0))
R> df
class increment has.increment
1 a 0 0
2 b 0 0
3 c 0 0
4 d 0 0
5 b 0 0
6 b 0 0
7 b 32 1
8 b 12 1
9 c 0 0
10 c 0 0
11 a 0 0
在存在增量的情况下获取每个班级的总数
N <- df %>% group_by(class,has.increment) %>% tally() %>% filter(has.increment == 1)
R> N
# A tibble: 1 x 3
# Groups: class [1]
class has.increment n
<chr> <dbl> <int>
1 b 1 2
然后加入:
merge(N,df, by = "class", all = TRUE)
R> merge(N,df, by = "class", all = TRUE)
class has.increment.x n increment has.increment.y
1 a NA NA 0 0
2 a NA NA 0 0
3 b 1 2 0 0
4 b 1 2 12 1
5 b 1 2 0 0
6 b 1 2 0 0
7 b 1 2 32 1
8 c NA NA 0 0
9 c NA NA 0 0
10 c NA NA 0 0
11 d NA NA 0 0
答案 0 :(得分:1)
尝试一下:
df %>%
group_by(class) %>%
mutate(increment_count_per_class = sum(increment!=0))