为每个子组应用函数

Question

我想知道如何使用循环函数来计算

apply(table(data$people,data$event),2,function(x) mean(x[x>0])) 

对于每个级别的颜色。我的意思是，我想为每个颜色级别计算上述函数。

people <-c("R1","R2","R2","R3","R3","R4","R4","R4","R4","R3","R3","R3","R3","R2","R2","R2","R5","R6")
event<-c("a","b","b","M","s","f","y","b","a","a","a","a","s","c","c","b","m","a")
Colour<-c("red","blue","green","pink","red","blue","grean","red","red","black","pink","blue","blue","green","blue","green","green","red")

data<-data.frame(people,event,Colour)

Answer 1

要对每个组执行函数，让我们首先将其设为函数：

your_function = function(data) {
    apply(table(data$people,data$event),2,function(x) mean(x[x>0]))
}

然后我们可以按颜色拆分您的数据并将您的函数应用于每个子数据帧：

dat_split = split(data, f = data$Colour)
results = lapply(dat_split, your_function)

results
# $black
#   a   b   c   f   m   M   s   y 
#   1 NaN NaN NaN NaN NaN NaN NaN 
#
# $blue
#   a   b   c   f   m   M   s   y 
#   1   1   1   1 NaN NaN   1 NaN 
#
# $grean
#   a   b   c   f   m   M   s   y 
# NaN NaN NaN NaN NaN NaN NaN   1 
# ...

就我个人而言，我觉得这不是很友好。 data.table 和 dplyr 使对数据帧子集的处理变得容易。我会从一开始就使用dplyr，就像这样：

library(dplyr)
data %>% group_by(people, Colour, event) %>%
    summarize(n = n()) %>%
    group_by(Colour, event) %>%
    summarize(mean = mean(n)) %>%
    tidyr::spread(key = event, value = mean)

# Source: local data frame [6 x 9]
#
#   Colour     a     b     c     f     m     M     s     y
#   (fctr) (dbl) (dbl) (dbl) (dbl) (dbl) (dbl) (dbl) (dbl)
# 1  black     1    NA    NA    NA    NA    NA    NA    NA
# 2   blue     1     1     1     1    NA    NA     1    NA
# 3  grean    NA    NA    NA    NA    NA    NA    NA     1
# ...