我想生成一个包含基于另一列中事件的索引的列，其中索引按日期排序。对于其他事件，将根据日期范围分配索引。索引应按单位ID分组。
数据由两个不同数据框的单位，事件和日期组成。一个数据框有一个名为＆＃34;整个文件＆＃34;的事件。当＆＃34;整个文件＆＃34;事件发生时，等级应该递增。然后，必须将排名转移到该单位的其他行以及该日期范围内。如果在第一个＆＃34;整个文件＆＃34;之前有事件。事件，这些事件的排名应为0。
在第一个数据框中，其中包含＆＃34;整个文件＆＃34;事件，如果单位编号改变，并且第一个事件不是＆＃34;整个文件＆＃34;，则开始事件具有前一个单元编号的最后一个等级。
然后必须按单位/日期范围将等级转移到后续数据帧。这就是我被困的地方
希望这个例子让问题清楚。
生成样本数据
set.seed(13)
# Ref http://stackoverflow.com/questions/14720983/efficiently-generate-a-random-sample-of-times-and-dates-between-two-dates
rDates <- function(N, st="2014/01/01", et="2014/10/01") {
st <- as.POSIXct(as.Date(st))
et <- as.POSIXct(as.Date(et))
dt <- as.numeric(difftime(et,st,unit="sec"))
ev <- sort(runif(N, 0, dt))
rt <- st + ev
}
nSamples_df1=100
nSamples_df2=75
df1<-data.frame(Event.Name=sample(c("Entire File",paste("Event ",letters[1:5])),nSamples_df1,replace=TRUE,prob=c(3,rep(1,5))),
unit=sample(1:10,nSamples_df1,replace=TRUE),
event_time = rDates(nSamples_df1))
df2<-data.frame(event=sample(c(paste("Event ",letters[6:10])),nSamples_df2,replace=TRUE),
unit=sample(1:10,nSamples_df2,replace=TRUE),
event_time = rDates(nSamples_df2))
第一步是订购数据，然后对＆＃34;整个文件＆＃34;进行排名。 df1中的事件。
# Put df1 in order
df1<-with(df1,head(df1[order(unit,event_time),],50))
# Extract and rank the "Entire File" events
entireFileEvents <- df1[df1$Event.Name=="Entire File",
c("Event.Name","unit","event_time")]
rankedEntireFileEvents <- transform(entireFileEvents,
fileEventIndex = ave(xtfrm(event_time), unit,
FUN = function(x) rank(x, ties.method = "first")))
将数据传输到原始数据框。我不确定这是否正确，排名是否最终位于正确的位置？
df1$fileEventIndex=NA
# Original risky assignment
# df1[df1$Event.Name=="Entire File","fileEventIndex"] <- rankedEntireFileEvents$fileEventIndex
# I'm not sure how to use merge in this case
# df1b <- merge(df1, rankedEntireFileEvents, by=c("Event.Name","unit","event_time"), sort = FALSE)
# Assignment using match, thanks akrun
match_rows <- match(paste(df1$Event.Name, df1$unit, df1$event_time),
paste(rankedEntireFileEvents$Event.Name, rankedEntireFileEvents$unit, rankedEntireFileEvents$event_time))
df1_match_rows = which(!is.na(match_rows))
refe_match_rows = match_rows[!is.na(match_rows)]
df1[df1_match_rows,"fileEventIndex"] <- rankedEntireFileEvents$fileEventIndex[refe_match_rows]
使用zoo
填写剩余的排名library(zoo)
df1<-na.locf(df1, na.rm = FALSE)
df1$fileEventIndex[is.na(df1$fileEventIndex)]=0
现在，我不知道如何将filesEventIndex从rankingEntireFileEvents传输到第二个数据帧。对于单位，如果日期较晚，则fileEventIndexin df2应具有相同的值。
以下是df1的当前结果。排名不正确，因为单位在＆＃34;整个文件＆＃34;之前发生了变化。发生了，因此第2单元的第一个事件排名为4，并且应该排名为0。
> with(df1,head(df1[order(unit,event_time),],50))
Event.Name unit event_time fileEventIndex
6 Entire File 1 2014-01-09 01:43:24 1
12 Event a 1 2014-01-23 10:25:59 1
26 Event c 1 2014-02-26 16:51:07 1
28 Event b 1 2014-03-04 05:39:57 1
47 Entire File 1 2014-05-05 02:19:16 2
67 Entire File 1 2014-07-01 18:52:56 3
76 Event a 1 2014-07-21 03:42:14 3
82 Event b 1 2014-08-07 16:33:33 3
87 Event a 1 2014-08-22 01:04:39 3
89 Entire File 1 2014-08-30 15:42:21 4
94 Event a 1 2014-09-07 13:46:25 4
8 Event e 2 2014-01-12 23:49:24 4 <-- This should be 1
16 Entire File 2 2014-01-27 10:20:28 1
21 Entire File 2 2014-02-11 17:24:22 2
22 Event c 2 2014-02-21 22:32:28 2
这是第二个df的方法，但结果不正确
df2$fileEventIndex=NA
units <- sort(unique(rankedEntireFileEvents$unit))
for (iu in seq(1,length(units))) {
uu = units[iu]
rankSameUnit = rankedEntireFileEvents$unit==uu
dfSameUnit = df2$unit == uu
uDates <- rankedEntireFileEvents[rankSameUnit,"event_time"]
uFileEventIndex <- rankedEntireFileEvents[rankSameUnit,"fileEventIndex"]
nDates = length(uDates)
if (nDates>0) {
dfBeforeFirstDate = df2$event_time < uDates[1]
df2_rows = dfSameUnit & dfBeforeFirstDate
if (any(df2_rows)) {
df2[df2_rows, "fileEventIndex"] = 0
}
for (id in seq(1,nDates-1)) {
dfAfterCurrentDate = df2$event_time >= uDates[id]
dfBeforeNextDate = df2$event_time < uDates[id]
currentRank = uFileEventIndex[id]
df2_rows = dfSameUnit & dfAfterCurrentDate & dfBeforeNextDate
if (any(df2_rows)) {
df2[df2_rows, "fileEventIndex" ] = currentRank
}
}
dfAfterLastDate = df2$event_time >= uDates[nDates]
df2_rows = dfSameUnit & dfAfterLastDate
if (any(df2_rows)) {
df2[df2_rows, "fileEventIndex"] = uFileEventIndex[nDates]
}
}
}
这是df2的输出，不应该有NA值
> with(df2,head(df2[order(unit,event_time),],50))
event unit event_time fileEventIndex
7 Event g 1 2014-01-18 05:39:10 NA
25 Event g 1 2014-03-25 01:56:28 NA
38 Event g 1 2014-04-29 09:57:39 NA
42 Event j 1 2014-05-17 05:39:30 NA
43 Event g 1 2014-05-23 05:07:06 NA
46 Event g 1 2014-06-03 07:12:13 NA
53 Event i 1 2014-06-25 21:51:25 NA
54 Event h 1 2014-06-30 00:41:00 NA
64 Event f 1 2014-08-05 06:28:56 NA
2 Event f 2 2014-01-03 03:27:28 0
12 Event h 2 2014-02-01 08:52:08 NA
27 Event i 2 2014-03-25 22:36:06 NA
39 Event f 2 2014-05-02 07:00:18 NA
44 Event f 2 2014-05-24 09:41:48 NA
47 Event j 2 2014-06-04 22:45:07 NA
50 Event g 2 2014-06-08 20:25:46 NA
58 Event j 2 2014-07-19 05:03:48 NA
67 Event h 2 2014-08-10 05:00:55 NA
22 Event h 3 2014-03-15 20:25:16 0
答案 0 :(得分：4)
执行此操作的一个不错的方法是在您的primaryEntireFileEvents条目上使用data.table滚动连接到主表。
library(data.table)
dt1<-data.table(df1)
dt2<-data.table(df2)
rankedEntireFileEvents.table <-data.table(rankedEntireFileEvents)
setkey(dt1,unit,event_time)
setkey(dt2,unit,event_time)
setkey(rankedEntireFileEvents.table, unit, event_time)
dt1.ranked <- rankedEntireFileEvents.table[dt1, roll=TRUE]
#some cleaning up to get your desired result
dt1.ranked$Event.Name <-NULL
setnames(dt1.ranked,"i.Event.Name","Event.Name")
#NA's in fileEventIndex indicte they precede fileEventIndex 1
dt2.ranked <- rankedEntireFileEvents.table[dt2, roll=TRUE]
现在表dt1.ranked和dt2.ranked是你想要的输出。