R使用data.table来剪切包含2个或更多变量的修复时间间隔

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
> 

我想计算每15分钟IN/OUT的计数数量,我可以通过创建另一个in_df,out_df,每15分钟切割这些数据帧,然后将它们合并在一起以获得我的结果来实现.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

我的问题是如何使用data.table来获得相同的结果？

Answer 1

在data.table中,我会这样做

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]

这使:

                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

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

1. 加入DT栏x上my_x.
2. 然后j对每个确定的子集做my_x.

在这种情况下,j=as.list(table(inOut)).该表必须被强制转换为列表以创建多个列(每个级别一个inOut).