我有数据框X01，其列应与mean，max和min
> 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
我的目标是在每列后添加min，max和mean。到目前为止，我已经通过重新排列列顺序手动完成了此操作，但我很快就会有包含许多列的数据，这使得这种方法非常慢：
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
R中是否有解决方案在一个步骤中处理每个列之后添加这些列，例如addmargins()？
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")
答案 0 :(得分：1)
这是尝试使用函数方法遍历每个列和函数：
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
答案 1 :(得分：1)
这是function restrictFile() {
var id = '10iM3V2q7FQWBAxy93eN9jvbp_SFco-KLPibeG9XRr71';
// get the file with the Advanced Drive API (REST V2)
var file = Drive.Files.get(id);
Logger.log('File "%s", restricted label was: %s', file.title, file.labels.restricted);
// set the restricted label
file.labels.restricted = true;
//update the file
Drive.Files.update(file, id);
// check the updated file
var updatedFile = Drive.Files.get(id);
Logger.log('File "%s", restricted label is: %s', updatedFile.title, updatedFile.labels.restricted);
}
方法：
dplyrlibrary(dplyr) X01 %>% mutate_all(funs(max, mean, min))
如果您想忽略 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
，则可以添加NA：
na.rm=TRUEX01[3,1] = NA X01 %>% mutate_all(funs(max, mean, min), na.rm=TRUE)
如果您只想将汇总值作为新数据框，则可以执行以下操作：
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
X01 %>% summarise_all(funs(max, mean, min), na.rm=TRUE)