除以R中按因子分组的变量的所有组合
我的数据如下所示:除以R中按因子分组的变量的所有组合,r,loops,dplyr,combinations,division,R,Loops,Dplyr,Combinations,Division,我的数据如下所示: set <- rep(c(1,2,3,4), each = 15) h_density <- rep(c(1,3,6), each =5 ) n_density <- rep(c(100,500,1000,5000,10000), times =4 ) counts <- runif(60,900,10000) data <- data.frame(set,h_density,n_density,counts) data$set <- as
set <- rep(c(1,2,3,4), each = 15)
h_density <- rep(c(1,3,6), each =5 )
n_density <- rep(c(100,500,1000,5000,10000), times =4 )
counts <- runif(60,900,10000)
data <- data.frame(set,h_density,n_density,counts)
data$set <- as.factor(data$set)
data$n_density <- as.factor(data$n_density)
data$h_density <- as.factor(data$h_density)
如何在R中实现这一点?如果您的数据不是太大,那么通过
internal\u join()
进行所有组合并通过n\u density
的不等性对其进行过滤是很好且简单的
library(dplyr)
data %>%
inner_join(data, by = c("set", "h_density"), suffix = c(".l", ".r")) %>%
filter(as.numeric(n_density.l) < as.numeric(n_density.r)) %>%
mutate(n_density_ratio = paste0(n_density.l , "/", n_density.r))
库(dplyr)
数据%>%
内部连接(数据,by=c(“set”,“h_density”),后缀=c(“.l”,“.r”)))%>%
过滤器(作为数值(n_density.l)<作为数值(n_density.r))%>%
突变(n_density_ratio=paste0(n_density.l,“/”,n_density.r))
library(dplyr)
data %>%
inner_join(data, by = c("set", "h_density"), suffix = c(".l", ".r")) %>%
filter(as.numeric(n_density.l) < as.numeric(n_density.r)) %>%
mutate(n_density_ratio = paste0(n_density.l , "/", n_density.r))