以編程方式添加摘要列

Question

我有數據框X01 ，我應該用mean ， max和min匯總

> head(X01)
  B01002e2 B01002e3
1     39.6     47.3
2     37.0     44.8
3     52.6     49.8
4     35.5     26.7
5     39.4     23.9
6     40.8     39.8

我的目標是在每一列之后添加min ， max和mean 。 到目前為止，我已經通過重新排列列順序來手動完成此操作，但是很快我將擁有包含許多列的數據，這會使這種方法非常緩慢：

X01$B01002e2_min <- min(X01$B01002e2, na.rm = TRUE)
X01$B01002e2_max <- max(X01$B01002e2, na.rm = TRUE)
X01$B01002e2_mean <- mean(X01$B01002e2, na.rm = TRUE)
X01$B01002e3_min <- min(X01$B01002e3, na.rm = TRUE)
X01$B01002e3_max <- max(X01$B01002e3, na.rm = TRUE)
X01$B01002e3_mean <- mean(X01$B01002e3, na.rm = TRUE)

X01 <- X01[ , c(1,3,4,5,2,6,7,8)]

> head(X01)
  B01002e2 B01002e2_min B01002e2_max B01002e2_mean B01002e3 B01002e3_min B01002e3_max
1     39.6            6         83.7    35.3427547     47.3          8.9         90.8
2     37.0            6         83.7    35.3427547     44.8          8.9         90.8
3     52.6            6         83.7    35.3427547     49.8          8.9         90.8
4     35.5            6         83.7    35.3427547     26.7          8.9         90.8
5     39.4            6         83.7    35.3427547     23.9          8.9         90.8
6     40.8            6         83.7    35.3427547     39.8          8.9         90.8
  B01002e3_mean
1    37.6894248
2    37.6894248
3    37.6894248
4    37.6894248
5    37.6894248
6    37.6894248

column being processed in one step, for example with addmargins() ? R中是否有一種解決方案，可以在一步處理addmargins() 列 ，例如使用addmargins()來添加這些列？

dput(head(X01))
    structure(list(B01002e2 = c(39.6, 37, 52.6, 35.5, 39.4, 40.8), 
        B01002e3 = c(47.3, 44.8, 49.8, 26.7, 23.9, 39.8)), .Names = c("B01002e2", 
    "B01002e3"), row.names = c(NA, 6L), class = "data.frame")

Answer 1

這是嘗試使用功能性方法遍歷每個列和功能的嘗試：

funs <- c("min","max","mean")
cbind(
  dat,
  unlist(Map(function(f,d) lapply(d,f), mget(funs, inherits=TRUE), list(dat) ), rec=FALSE)
)
#  B01002e2 B01002e3 min.B01002e2 min.B01002e3 max.B01002e2 max.B01002e3 mean.B01002e2 mean.B01002e3
#1     39.6     47.3         35.5         23.9         52.6         49.8      40.81667      38.71667
#2     37.0     44.8         35.5         23.9         52.6         49.8      40.81667      38.71667
#3     52.6     49.8         35.5         23.9         52.6         49.8      40.81667      38.71667
#4     35.5     26.7         35.5         23.9         52.6         49.8      40.81667      38.71667
#5     39.4     23.9         35.5         23.9         52.6         49.8      40.81667      38.71667
#6     40.8     39.8         35.5         23.9         52.6         49.8      40.81667      38.71667

Answer 2

這是dplyr方法：

library(dplyr)

X01 %>% mutate_all(funs(max, mean, min))

  B01002e2 B01002e3 B01002e2_max B01002e3_max B01002e2_mean B01002e3_mean B01002e2_min B01002e3_min 1 39.6 47.3 52.6 49.8 40.81667 38.71667 35.5 23.9 2 37.0 44.8 52.6 49.8 40.81667 38.71667 35.5 23.9 3 52.6 49.8 52.6 49.8 40.81667 38.71667 35.5 23.9 4 35.5 26.7 52.6 49.8 40.81667 38.71667 35.5 23.9 5 39.4 23.9 52.6 49.8 40.81667 38.71667 35.5 23.9 6 40.8 39.8 52.6 49.8 40.81667 38.71667 35.5 23.9 

如果要忽略NA則可以添加na.rm=TRUE ：

X01[3,1] = NA

X01 %>% mutate_all(funs(max, mean, min), na.rm=TRUE)

  B01002e2 B01002e3 B01002e2_max B01002e3_max B01002e2_mean B01002e3_mean B01002e2_min B01002e3_min 1 39.6 47.3 40.8 49.8 38.46 38.71667 35.5 23.9 2 37.0 44.8 40.8 49.8 38.46 38.71667 35.5 23.9 3 NA 49.8 40.8 49.8 38.46 38.71667 35.5 23.9 4 35.5 26.7 40.8 49.8 38.46 38.71667 35.5 23.9 5 39.4 23.9 40.8 49.8 38.46 38.71667 35.5 23.9 6 40.8 39.8 40.8 49.8 38.46 38.71667 35.5 23.9 

如果僅要將摘要值用作新的數據框，則可以執行以下操作：

X01 %>% summarise_all(funs(max, mean, min), na.rm=TRUE)

  B01002e2_max B01002e3_max B01002e2_mean B01002e3_mean B01002e2_min B01002e3_min 1 40.8 49.8 38.46 38.71667 35.5 23.9