I have a data.frame that looks like this
> head(df)
Memory Memory Memory Memory Memory Naive Naive
10472501 6.075714 5.898929 6.644946 6.023901 6.332126 8.087944 7.520194
10509163 6.168941 6.495393 5.951124 6.052527 6.404401 7.152890 8.335509
10496091 10.125575 9.966211 10.075613 10.310952 10.090649 11.803949 11.274480
10427035 6.644921 6.658567 6.569745 6.499243 6.990852 8.010784 7.798154
10503695 8.379494 8.153917 8.246484 8.390747 8.346748 9.540236 9.091740
10451763 10.986717 11.233819 10.643245 10.230697 10.541396 12.248487 11.823138
我希望找到Memory
列和Naive
列的平均值。 aggregate
函数用于聚合行。这个data.frame
可能有大量的行,因此转置然后按原始data.frame
的colnames
应用aggregate
似乎不太好,而且通常很烦人:
> head(t(aggregate(t(df),list(colnames(df)), mean)))
[,1] [,2]
Group.1 "Memory" "Naive"
10472501 "6.195123" "8.125439"
10509163 "6.214477" "7.733625"
10496091 "10.11380" "11.55348"
10427035 "6.672665" "8.266854"
10503695 "8.303478" "9.340436"
我错过了什么非常明显的事情吗?