ř使用data.table切割含有2或更多个变量

Question

我有一个数据帧

df <- data.frame(time = c("2015-09-07 00:32:19", "2015-09-07 01:02:30", "2015-09-07 01:31:36", "2015-09-07 01:47:45", 
"2015-09-07 02:00:17", "2015-09-07 02:07:30", "2015-09-07 03:39:41", "2015-09-07 04:04:21", "2015-09-07 04:04:21", "2015-09-07 04:04:22"), 
inOut = c("IN", "OUT", "IN", "IN", "IN", "IN", "IN", "OUT", "IN", "OUT")) 

> df 
        time inOut 
1 2015-09-07 00:32:19 IN 
2 2015-09-07 01:02:30 OUT 
3 2015-09-07 01:31:36 IN 
4 2015-09-07 01:47:45 IN 
5 2015-09-07 02:00:17 IN 
6 2015-09-07 02:07:30 IN 
7 2015-09-07 03:39:41 IN 
8 2015-09-07 04:04:21 OUT 
9 2015-09-07 04:04:21 IN 
10 2015-09-07 04:04:22 OUT 
> 

我想要计算计数IN/OUT每15分钟的数量， 我可以做修复时间间隔这通过创建另一个in_df，out_df，每15分钟剪切一次这些数据帧，然后将它合并到一起以获得我的结果。 outdf是我的预期结果。

in_df <- df[which(df$inOut== "IN"),] 
out_df <- df[which(df$inOut== "OUT"),] 

a <- data.frame(table(cut(as.POSIXct(in_df$time), breaks="15 mins"))) 
b <- data.frame(table(cut(as.POSIXct(out_df$time), breaks="15 mins"))) 
colnames(b) <- c("Time", "Out") 
colnames(a) <- c("Time", "In") 

outdf <- merge(a,b, all=TRUE) 
outdf[is.na(outdf)] <- 0 

> outdf 
        Time In Out 
1 2015-09-07 00:32:00 1 0 
2 2015-09-07 00:47:00 0 0 
3 2015-09-07 01:02:00 0 1 
4 2015-09-07 01:17:00 1 0 
5 2015-09-07 01:32:00 0 0 
6 2015-09-07 01:47:00 2 0 
7 2015-09-07 02:02:00 1 0 
8 2015-09-07 02:17:00 0 0 
9 2015-09-07 02:32:00 0 0 
10 2015-09-07 02:47:00 0 0 
11 2015-09-07 03:02:00 0 0 
12 2015-09-07 03:17:00 0 0 
13 2015-09-07 03:32:00 1 0 
14 2015-09-07 03:47:00 0 0 
15 2015-09-07 04:02:00 1 2 

我的问题是如何用data.table做到这一点，以获得相同的结果？

Answer 1

在data.table，我会做

library(data.table) 
setDT(df) 

df[, timeCut := cut(as.POSIXct(time), breaks="15 mins")] 

df[J(timeCut = levels(timeCut)), 
    as.list(table(inOut)), 
    on = "timeCut", 
    by = .EACHI] 

这给：

   timeCut IN OUT 
1: 2015-09-07 00:32:00 1 0 
2: 2015-09-07 00:47:00 0 0 
3: 2015-09-07 01:02:00 0 1 
4: 2015-09-07 01:17:00 1 0 
5: 2015-09-07 01:32:00 0 0 
6: 2015-09-07 01:47:00 2 0 
7: 2015-09-07 02:02:00 1 0 
8: 2015-09-07 02:17:00 0 0 
9: 2015-09-07 02:32:00 0 0 
10: 2015-09-07 02:47:00 0 0 
11: 2015-09-07 03:02:00 0 0 
12: 2015-09-07 03:17:00 0 0 
13: 2015-09-07 03:32:00 1 0 
14: 2015-09-07 03:47:00 0 0 
15: 2015-09-07 04:02:00 1 2 

说明最后一部分是像DT[i=J(x=my_x), j, on="x", by=.EACHI]，可以理解为：

1. 加入DT列x on my_x。
2. 然后对由my_x确定的每个子集执行j。

在这种情况下，j=as.list(table(inOut))。该表必须被强制为一个列表来创建多个列（每个级别为inOut）。