SP.FieldUserValue.fromUser()
使用dplyr按计数创建类别和顺序的计数。
#Generate some data
set.seed(1234)
rows = 100
created_data <- data.frame(index = 1:rows,
catsA = sample((letters[1:5]),rows,replace=T),
valueA = round(rnorm(rows),3))
输出
library(dplyr)
count_of_cat <- created_data %>%
group_by(catsA) %>%
summarise(rowcount = n()) %>%
ungroup %>%
arrange(-rowcount) %>%
mutate(rel.freq = round(rowcount/sum(rowcount),3)) %>%
mutate(cum.freq = cumsum(rel.freq))
在说出cum.freq&gt;之后是否有一个很好的方法来汇总行0.50
期望的输出
catsA rowcount rel.freq cum.freq
1 b 26 0.26 0.26
2 a 25 0.25 0.51
3 c 17 0.17 0.68
4 d 17 0.17 0.85
5 e 15 0.15 1.00
答案 0 :(得分:1)
从这里开始dplyr mutate rowSums calculations or custom functions
count_of_cat %>% filter(cum.freq <= 0.51) %>%
rbind(
count_of_cat %>% filter(cum.freq > 0.51) %>%
summarise(catsA = "new",
rowcount = sum(rowcount),
rel.freq = sum(rel.freq),
cum.freq = 1.00)
)