r语言 - 计算多列具有相同值的行的最小平均值最大值

Question

在下面的数据集中，我想首先检查哪些行对列U和T具有相同的值。对于所有这些行，我想计算Mean列的平均值，Min列的最小值和Max列的最大值。

如果列 U 和 T 具有相同值的行是单独的data.frame()，我可以轻松做到这一点，但在这种情况下，我首先需要提取所有此类子data.frame() in data.frame()，然后执行操作。

如果有人有更好的方法使用R库，请建议？

输入数据

data <- structure(list(A = c(0.1, 0.1, 0.1, 0.1), B = c(NA, NA, NA, NA
), C = structure(c(1L, 1L, 1L, 1L), .Label = "Yes", class = "factor"), 
    U = c(11L, 11L, 11L, 11L), T = structure(c(1L, 1L, 1L, 1L
    ), .Label = "A", class = "factor"), P = structure(c(1L, 1L, 
    1L, 1L), .Label = "INT", class = "factor"), Q = 1:4, R = c(0L, 
    0L, 0L, 0L), S = c(1L, 1L, 1L, 1L), W = structure(c(1L, 1L, 
    1L, 1L), .Label = "A", class = "factor"), Mean = c(21.208, 
    21.22333333, 21.23666667, 21.174), Min = c(21.02, 21.01, 
    21.09, 21.02), Max = c(21.35, 21.39, 21.47, 21.36)), class = "data.frame", row.names = c(NA, 
-4L))

预期输出

A   B   C   U   T   P   Q   R   S   T   Mean    Min     Max
0.1 NA  Yes 11  A   INT 4   0   1   A   21.2105 21.01   21.47

Answer 1

我们可以使用

library(tidyverse)
data %>% 
  group_by(U, T) %>%
  mutate(Mean = mean(Mean), Min = min(Min), Max = max(Max))%>% 
  slice(1)

Answer 2

nm = names(data)[!names(data) %in% c("Mean", "Min", "Max")]
do.call(rbind, lapply(split(data, paste(data$U, data$T)), function(x){
    data.frame(x[1, nm], Mean = mean(x$Mean), Min = min(x$Min), Max = max(x$Max))
}))
#       A  B   C  U T   P Q R S W    Mean   Min   Max
#11 A 0.1 NA Yes 11 A INT 1 0 1 A 21.2105 21.01 21.47