如何检测和重新插入缺失的数据？ [英] How do I detect and re-insert missing data?

问题描述

我在数据表中缺少一行，描述时间， sid 和 sc 到 count ：

I have a missing row in a data table which describes a function from time, sid, and s.c to count:

> dates.dt[1001:1011]
        sid   s.c  count                time
 1: missing CLICK 104192 2013-05-25 10:00:00
 2: missing SHARE   7694 2013-05-25 10:00:00
 3: present CLICK  99573 2013-05-25 10:00:00
 4: present SHARE  89302 2013-05-25 10:00:00
 5: missing CLICK     28 2013-05-25 11:00:00
 6: present CLICK     25 2013-05-25 11:00:00
 7: present SHARE     15 2013-05-25 11:00:00
 8: missing CLICK 104544 2013-05-25 12:00:00
 9: missing SHARE   7253 2013-05-25 12:00:00
10: present CLICK 105891 2013-05-25 12:00:00
11: present SHARE  88709 2013-05-25 12:00:00

缺少的行是（我预期第一列和第二列以及每个时间片的两个值中的每一行都有一行）：

the missing row is (I expect a row for each of the two values of the 1st and 2nd columns and each time slice):

    missing SHARE      0 2013-05-25 11:00:00

我如何检测并恢复这样缺失的行？

How do I detect and restore such missing rows?

我发现这是

library(data.table)
total <- dates.dt[, list(sum(count)) , keyby="time"]
setnames(total,"V1","total")
ts <- dates.dt[s.c=="SHARE" & sid=="missing", list(sum(count)) , keyby="time"]
cat("SHARE/missing:",nrow(ts),"rows\n")
stopifnot(identical(total$time,ts$time)) # --> ERROR!
total$shares.missing <- ts$V1

找到 ts $ time 和 total $ time
不同并插入0行的第一个位置，但是这似乎是一个相当乏味的
过程。

Now, I guess I can find the first place where ts$time and total$time differ and insert a 0 row there, but this seems like a rather tedious process.

谢谢！

推荐答案

按照Frank的建议，您可以这样做：

Following @Frank's suggestion you can do:

setkey(dt, time, sid, s.c)
dt[J(expand.grid(unique(time),unique(sid),unique(s.c)))][order(time, sid, s.c)]
#                   time     sid   s.c  count
# 1: 2013-05-25 10:00:00 missing CLICK 104192
# 2: 2013-05-25 10:00:00 missing SHARE   7694
# 3: 2013-05-25 10:00:00 present CLICK  99573
# 4: 2013-05-25 10:00:00 present SHARE  89302
# 5: 2013-05-25 11:00:00 missing CLICK     28
# 6: 2013-05-25 11:00:00 missing SHARE     NA
# 7: 2013-05-25 11:00:00 present CLICK     25
# 8: 2013-05-25 11:00:00 present SHARE     15
# 9: 2013-05-25 12:00:00 missing CLICK 104544
#10: 2013-05-25 12:00:00 missing SHARE   7253
#11: 2013-05-25 12:00:00 present CLICK 105891
#12: 2013-05-25 12:00:00 present SHARE  88709

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