我想在数据框中创建一个变量,该变量将根据列的Quartile / Median值对观察值进行分类。
以下是我的尝试。
Name<-c("name1","name2","name3","name4","name5","name6")
Age<-c(49,12,29,55,25,19)
df9<-data.frame(Name,Age)
df9$catoG[df9$Age<=quantile(df9$Age,0.25)]<-"Young"
df9$catoG[df9$Age>quantile(df9$Age,0.25) & df9$Age<=median(df9$Age)]<-"Adult"
df9$catoG[df9$Age>median(df9$Age)]<-"Elder"
我收到的输出是
Name Age catoG
1 name1 49 Elder
2 name2 12 Young
3 name3 29 Elder
4 name4 55 Elder
5 name5 25 Adult
6 name6 19 Young
在R中是否有更高效的方法可以实现相同的目标?
cut
是您在范围内拆分向量的所有任务的朋友:
df9$new = cut(df9$Age,
breaks = c(-Inf, quantile(df9$Age,c(0.25, 0.5)), Inf),
labels = c('Young', 'Adult', 'Elder') )
# Name Age catoG new
#1 name1 49 Elder Elder
#2 name2 12 Young Young
#3 name3 29 Elder Elder
#4 name4 55 Elder Elder
#5 name5 25 Adult Adult
#6 name6 19 Young Young
你可以使用dplyr::mutate
包中的dplyr::case_when
和dplyr
:
Name<-c("name1","name2","name3","name4","name5","name6")
Age<-c(49,12,29,55,25,19)
df9<-data.frame(Name,Age)
df9 %>% mutate(catoG = case_when(Age<=quantile(Age,0.25) ~ 'Young',
Age>quantile(Age,0.25) & Age<=median(Age) ~ 'Adult',
TRUE ~ 'Elder'))