我有五个大约有60列的数据框需要合并。它们每个都有相同的列，并且由于它们代表相同的值，我正在使用它们的平均值进行合并。问题不在于能否将它们组合在一起，而在于如何高效地这样做。以下是示例数据/代码：
#reproducible random data
set.seed(123)
dat1 <- data.frame( a = rnorm(16), b = rnorm(16), c = rnorm(16), d = rnorm(16), e = rnorm(16), f = rnorm(16))
dat2 <- data.frame( a = rnorm(16), b = rnorm(16), c = rnorm(16), d = rnorm(16), e = rnorm(16), f = rnorm(16))
dat3 <- data.frame( a = rnorm(16), b = rnorm(16), c = rnorm(16), d = rnorm(16), e = rnorm(16), f = rnorm(16))
#This works but is inefficient
final_data<-data.frame(a=rowMeans(cbind(dat1$a,dat2$a,dat3$a)),
b=rowMeans(cbind(dat1$b,dat2$b,dat3$b)),
c=rowMeans(cbind(dat1$c,dat2$c,dat3$c)),
d=rowMeans(cbind(dat1$d,dat2$d,dat3$d)),
e=rowMeans(cbind(dat1$e,dat2$e,dat3$e)),
f=rowMeans(cbind(dat1$f,dat2$f,dat3$f))
)
#what results should look like
head(final_data)
# a b c d e f
# 1 0.573813625 0.17695841 -0.1434628 -0.53673101 0.353906578 0.24262067
# 2 0.135689926 -0.69206908 0.2888584 -0.37215810 -0.038298083 -0.23317107
# 3 0.004068807 0.44666945 0.5205118 0.09587453 -0.308528454 0.30516883
# 4 0.347100292 0.02401646 0.1409754 -0.15931120 0.587047386 -0.08684867
# 5 0.006529998 0.09010946 0.4932670 0.62606230 -0.005235813 -0.36967000
# 6 0.240225778 -0.45824825 -0.5000004 0.66131121 0.619480608 0.55650611
这里的问题是我不想为新数据框中的60列都重新编写
a=rowMeans(cbind(dat1$a,dat2$a,dat3$a))。您能想到一个好的方法来解决这个问题吗？编辑：我将接受以下答案，因为它允许我设置要应用该操作的列-
final_data1<-as.data.frame(sapply(colnames(dat1),function(i)
rowMeans(cbind(dat1[,i],dat2[,i],dat3[,i]))))
> identical(final_data1,final_data)
[1] TRUE
set.seed，这样我们就可以更轻松地匹配所需的输出。 - David Arenburg