处理大量行

【问题标题】：Dealing with a huge amount of rows处理大量行
【发布时间】：2021-04-08 21:46:58
【问题描述】：

我有 1000 万行长的数据。我删除了多余的年份和列。

为了减少它，我想运行：DT<- setDT(DT)[, lapply(Filter(is.numeric,.SD), sum, na.rm=TRUE), by = .(State_Ab, County_Code, year, Sex, Age)]（我删除了其他子类型（种族），我想总结剩下的类型）。

但是代码会一直运行下去。我怎样才能更有效地做到这一点？

例如先转换变量？ （我删除了一些已经希望提高效率的列。我可以在求和之前先转换这些列）。

DT <- structure(list(year = c(1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994, 
1994, 1994, 1994), State_Ab = c("AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL"), County_Code = c(1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3), Sex = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2), Age = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 
30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 
46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 
62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 
78, 79, 80, 81, 82, 83, 84, 85, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 
26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 
42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 
58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 0, 1, 2, 4, 6, 
7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 20, 22, 23, 26, 27, 
28, 29, 30, 32, 33, 34, 35, 36, 38, 40, 41, 42, 43, 45, 47, 48, 
49, 50, 51, 55, 56, 64, 65, 74, 84, 0, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 24, 26, 27, 28, 29, 
31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 47, 48, 
49, 50, 51, 53, 54, 56, 58, 60, 61, 62, 74, 0, 1, 2, 3, 4, 5, 
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 
39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 
55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 
71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 0, 
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 
19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 
51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 
83, 84, 85, 8, 14, 15, 30, 37, 48, 55, 75, 1, 8, 10, 16, 25, 
35, 45, 50, 65, 75, 7, 12, 15, 18, 20, 25, 28, 31, 32, 33, 40, 
42, 43, 45, 51, 53, 57, 59, 60, 65, 3, 4, 6, 10, 13, 14, 15, 
16, 18, 21, 30, 31, 35, 38, 39, 40, 41, 44, 46, 48, 51, 52, 59, 
60, 65, 70, 75, 0, 2, 3, 4, 7, 8, 11, 13, 14, 16, 17, 18, 20, 
21, 22, 23, 28, 32, 36, 37, 40, 43, 44, 47, 55, 0, 1, 2, 4, 7, 
8, 11, 13, 14, 15, 17, 18, 21, 23, 24, 28, 29, 31, 32, 33, 34, 
36, 37, 38, 39, 41, 42, 43, 45, 47, 49, 50, 52, 54, 55, 57, 58, 
59, 62, 33, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 
31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 
47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 
63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 
79, 80, 81, 82, 83, 84, 85, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 
27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 
43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 0, 1, 2, 3, 4, 5, 
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 
39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 
55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 
73, 74, 77, 78, 79, 80, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 
44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 
60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 
76, 77, 78, 80, 81, 84, 85, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 
27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 
43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 0, 1, 2, 3, 4, 5, 
6, 7, 8, 9), Population = c(224, 209, 220, 249, 228, 243, 227, 
228, 247, 277, 279, 262, 245, 263, 269, 238, 226, 250, 206, 185, 
175, 155, 168, 223, 208, 200, 190, 201, 195, 225, 249, 233, 268, 
243, 240, 273, 268, 272, 253, 272, 262, 249, 241, 206, 241, 248, 
231, 246, 163, 185, 188, 192, 173, 169, 163, 156, 157, 159, 131, 
147, 133, 115, 127, 112, 112, 122, 111, 97, 82, 75, 78, 78, 64, 
76, 51, 59, 50, 43, 38, 26, 32, 28, 22, 22, 18, 58, 212, 216, 
221, 213, 221, 203, 235, 219, 216, 227, 219, 230, 225, 240, 229, 
214, 236, 241, 192, 169, 157, 160, 164, 200, 212, 193, 221, 224, 
206, 229, 241, 237, 273, 246, 278, 277, 309, 268, 247, 279, 265, 
261, 246, 221, 241, 239, 226, 249, 181, 180, 204, 206, 161, 182, 
175, 161, 162, 158, 150, 148, 125, 127, 127, 130, 111, 107, 108, 
120, 109, 107, 104, 93, 99, 86, 79, 70, 75, 75, 68, 59, 63, 47, 
51, 46, 39, 202, 2, 4, 5, 2, 4, 1, 4, 4, 2, 2, 2, 5, 4, 4, 3, 
2, 2, 4, 4, 6, 2, 3, 1, 6, 1, 6, 1, 6, 1, 5, 2, 2, 1, 4, 3, 1, 
1, 3, 2, 2, 1, 3, 7, 1, 1, 3, 2, 3, 5, 3, 4, 1, 2, 3, 3, 5, 2, 
1, 1, 4, 3, 2, 3, 3, 3, 2, 5, 5, 2, 1, 2, 2, 1, 3, 6, 4, 3, 4, 
2, 3, 3, 1, 3, 1, 3, 2, 3, 3, 4, 2, 2, 1, 2, 4, 2, 2, 1, 1, 48, 
63, 71, 64, 73, 64, 57, 63, 64, 70, 63, 68, 75, 76, 83, 85, 76, 
84, 74, 70, 56, 54, 43, 48, 47, 41, 38, 47, 38, 49, 45, 39, 47, 
42, 45, 43, 41, 57, 49, 50, 47, 46, 50, 46, 28, 35, 33, 34, 29, 
27, 26, 32, 23, 22, 22, 21, 25, 18, 19, 17, 23, 23, 18, 18, 23, 
16, 21, 21, 17, 18, 13, 16, 11, 18, 15, 9, 12, 15, 8, 12, 11, 
8, 3, 3, 9, 27, 59, 71, 67, 65, 60, 65, 63, 73, 58, 61, 61, 61, 
76, 87, 77, 79, 80, 87, 67, 66, 54, 64, 60, 55, 57, 59, 53, 52, 
53, 48, 52, 59, 52, 58, 61, 67, 56, 60, 62, 52, 59, 52, 54, 54, 
52, 58, 41, 29, 25, 34, 32, 31, 30, 23, 28, 28, 31, 26, 24, 28, 
26, 26, 24, 31, 24, 26, 28, 30, 27, 21, 19, 22, 28, 23, 18, 16, 
18, 19, 16, 11, 19, 17, 17, 11, 11, 73, 1, 3, 1, 1, 2, 2, 1, 
2, 3, 1, 1, 2, 1, 1, 2, 4, 1, 1, 4, 3, 4, 2, 4, 1, 2, 1, 2, 2, 
4, 1, 2, 4, 1, 2, 2, 3, 1, 1, 2, 2, 4, 3, 5, 2, 1, 1, 3, 2, 2, 
2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 3, 3, 2, 1, 2, 3, 2, 2, 1, 3, 
1, 1, 2, 1, 2, 2, 1, 1, 3, 2, 1, 2, 5, 2, 4, 2, 2, 1, 4, 2, 2, 
3, 1, 1, 2, 2, 2, 1, 2, 1, 2, 2, 4, 1, 1, 3, 2, 3, 2, 2, 2, 2, 
3, 6, 3, 3, 3, 4, 3, 3, 4, 3, 2, 7, 4, 1, 1, 3, 10, 2, 611, 619, 
644, 642, 678, 644, 665, 670, 650, 693, 710, 679, 711, 737, 764, 
754, 732, 707, 584, 532, 502, 496, 489, 580, 602, 610, 556, 587, 
587, 617, 728, 700, 696, 731, 762, 787, 802, 804, 715, 791, 805, 
740, 735, 720, 730, 736, 726, 801, 562, 595, 624, 623, 560, 548, 
509, 526, 548, 513, 484, 565, 479, 489, 512, 541, 515, 553, 545, 
561, 498, 472, 489, 455, 443, 429, 349, 320, 303, 286, 259, 217, 
221, 173, 139, 135, 117, 419, 597, 576, 606, 628, 644, 608, 617, 
595, 604, 613, 647, 668, 691, 675, 685, 665, 649, 666, 539, 535, 
483, 464, 523, 617, 615, 598, 622, 636, 600, 689, 720, 717, 747, 
768, 785, 803, 817, 814, 751, 821, 800, 740, 734, 753, 756, 803, 
770, 811, 580, 643, 664, 646, 567, 573, 557, 570, 580, 546, 524, 
583, 520, 540, 571, 589, 593, 590, 574, 565, 536, 538, 511, 479, 
483, 466, 430, 405, 380, 362, 339, 306, 289, 275, 231, 234, 212, 
980, 14, 13, 16, 13, 16, 10, 9, 11, 8, 12, 13, 8, 9, 14, 14, 
12, 15, 12, 14, 13, 11, 21, 14, 15, 13, 7, 20, 9, 11, 10, 11, 
14, 11, 14, 10, 8, 15, 7, 10, 10, 11, 11, 13, 7, 7, 6, 7, 7, 
11, 6, 3, 9, 7, 3, 5, 3, 4, 5, 6, 6, 3, 6, 5, 7, 9, 4, 4, 1, 
3, 1, 3, 4, 1, 1, 2, 3, 3, 13, 14, 14, 14, 14, 10, 7, 7, 9, 9, 
14, 12, 10, 9, 10, 10, 8, 10, 13, 7, 11, 9, 5, 7, 8, 11, 12, 
13, 8, 10, 9, 8, 8, 10, 12, 12, 14, 11, 9, 7, 9, 8, 7, 7, 9, 
11, 8, 12, 4, 4, 9, 10, 5, 7, 4, 5, 7, 5, 6, 4, 3, 3, 3, 4, 3, 
4, 5, 3, 5, 2, 2, 1, 2, 5, 1, 4, 1, 2, 1, 2, 4, 2, 3, 125, 138, 
129, 132, 140, 127, 132, 130, 120, 149, 150, 128, 153, 140, 160, 
140, 148, 155, 133, 133, 122, 107, 91, 92, 93, 94, 84, 87, 84, 
104, 101, 88, 74, 85, 98, 100, 97, 94, 92, 112, 99, 75, 86, 69, 
82, 69, 67, 61, 37, 49, 46, 51, 42, 40, 44, 52, 47, 39, 42, 31, 
47, 36, 39, 36, 37, 39, 36, 34, 29, 31, 26, 23, 30, 27, 22, 28, 
22, 15, 15, 20, 22, 13, 19, 12, 10, 59, 127, 138, 141, 141, 132, 
134, 119, 122, 113, 130)), class = c("data.table", "data.frame"
), row.names = c(NA, -1000L), spec = structure(list(cols = list(
    X1 = structure(list(), class = c("collector_double", "collector"
    )), X2 = structure(list(), class = c("collector_character", 
    "collector")), X3 = structure(list(), class = c("collector_character", 
    "collector")), X4 = structure(list(), class = c("collector_character", 
    "collector")), X5 = structure(list(), class = c("collector_double", 
    "collector")), X6 = structure(list(), class = c("collector_double", 
    "collector")), X7 = structure(list(), class = c("collector_double", 
    "collector")), X8 = structure(list(), class = c("collector_double", 
    "collector")), X9 = structure(list(), class = c("collector_character", 
    "collector")), X10 = structure(list(), class = c("collector_character", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
"collector")), skip = 0), class = "col_spec"))

【问题讨论】：

  • 当您说“为了修剪它”时，您希望执行什么操作？为什么要按组执行性别或年龄的总和？
  • 我想将数据减少到我真正需要的部分。例如，我删除了两个额外的子类型列。通过将人口与其余类型相加，我将删除冗余数据。这两列都有 3 种类型。这意味着我可以通过对剩余类型求和来将行数减少 3x3 = 9。
  • @IanCampbell 数据代表计数数据，每个子组，每个县。
  • DT[,Population := sum(Population, na.rm=TRUE), by = .(State_Ab, County_Code, year, Sex, Age)] 应该会更快，因为您可以节省大量调度时间。
  • 你也可以使用dt[, .SD, .SDcols = is.numeric]，我要强调的是，我们可以提前告诉data.table在.SD中使用哪些列.SDcols = ...

标签： r performance data.table


【解决方案1】：

.SD 如果未优化，可能会非常慢。这里速度缓慢的一个原因是它正在确定要为数据中的每个组独立包含哪些列。试试这个作为替代方案：

DT2 <- DT[, lapply(.SD, sum, na.rm=TRUE), by = .(State_Ab, County_Code, year, Sex, Age), verbose=T]

应该为您的最终代码删除verbose=T，但有助于理解。这里展示了使用更简单的 lapply 形式的好处：lapply optimization changed j from 'lapply(.SD, sum, na.rm = TRUE)' to 'list(sum(Population, na.rm = TRUE))'。此优化不适用于原始代码。

[不必要的细节：这种形式允许使用gsum 在后台进一步优化表达式。这意味着 R 不必将数百万组中的每一个都传递给 sum 函数，它可以一次传递整个事物，从而节省了一大堆开销。]

如果您有不想要的非数字列，您可以预先删除它们或使用 .SDcols 来识别它们一次（而不是每组一次）。

【讨论】：

  • 请注意，您可以提供.SDcols=is.numeric 来简洁地处理列过滤
猜你喜欢
  • 1970-01-01
  • 1970-01-01
  • 2012-10-27
  • 2012-05-14
  • 2011-05-16
  • 2014-04-23
  • 2013-01-31
  • 2017-02-09
  • 1970-01-01
相关资源
最近更新 更多
热门标签
Java Python linux javascript Mysql C# Docker 算法 前端 SpringBoot Redis Vue spring 设计模式 .net core .net kubernetes c++ 数据库 数据结构 大数据 js 机器学习 微服务 Android Go 程序员 面试 JVM ASP.net core 云原生 人工智能 后端 PHP git CSS golang k8s Nginx Django mybatis 深度学习 多线程 React 架构 devops 爬虫 云计算 Spring Boot LeetCode