使用一个数据集上的一列中的日期设置一年范围（向前），以查找与 R 中的 id 匹配的不同数据集上的日期
[英]setting a one year range (forward) using dates in one column on one dataset to find dates on a different dataset matching by id in R
问题描述
我有两个数据集，（dt1）一个具有“开始”日期，每个单独的 ID 最多两个条目（因为这些是 L 或 R 眼中的手术条目）和一个（dt2）第二个数据库，前后有多个日期开始日期。 这些不仅限于眼科手术，还包括任何其他医疗保健访问。 我想在我的数据集中的所有 id 中查找手术 L 和 R 开始日期后一年内的事件。 如果他们有结果，我想通过横向匹配他们。 如果他们没有，那么在一年内的最后一次访问中没有偏侧匹配（lat）。 先前的结果只是开始日期之前的结果或“事件”的数量，即先前结果的总和。
id lat year status date
1 le 18 1 2018-07-06
1 re 11 1 2011-04-12
2 le 15 0 2015-01-10
2 re 11 0 2011-07-20
3 NA 10 1 2010-02-18
3 bilat 13 1 2013-09-26
id lat outcome date year
1: 1 NA 0 2015-07-06 15
2: 1 le 0 2019-04-03 19
3: 1 le 1 2019-04-30 19
4: 1 re 1 2011-07-14 11
5: 1 re 1 2015-09-10 15
6: 1 re 1 2008-07-14 8
7: 2 NA 0 2015-11-10 15
8: 2 re 0 2012-04-23 12
9: 2 NA 0 2015-02-18 15
10: 2 57 0 2008-12-01 8
11: 3 57 0 2014-01-15 14
12: 3 NA 0 2014-02-21 14
13: 3 bilat 1 2014-02-28 14
我希望决赛桌看起来像这样
id lat year status date outcome end_date prior_outcome
1 le 18 1 2018-07-06 1 2019-04-30 3
1 re 11 1 2011-04-12 1 2011-07-14 1
2 le 15 0 2015-01-10 0 2015-11-10 0
2 re 11 0 2011-07-20 0 2012-04-23 0
3 NA 10 1 2010-02-18 0 <NA> 0
3 bilat 13 1 2013-09-26 1 2014-02-28 0
这是数据集的代码
dates <- as.Date(c("2018-07-06","2011-04-12",
"2015-01-10","2011-07-20",
"2010-02-18","2013-09-26"))
dt1 <- data.table(id=c(1,1,2,2,3,3),
lat=c("le","re","le","re","NA", "bilat"),
year= c(18, 11,15,11,10,13),
status=status <- c(1,1,0,0,1,1),
date= dates)
dates2 <- as.Date(c('2015-07-06',
'2019-04-03',
'2019-04-30',
'2011-07-14',
'2015-09-10',
'2008-07-14',
'2015-11-10',
'2012-04-23',
'2015-02-18',
'2008-12-01',
'2014-01-15',
'2014-02-21',
'2014-02-28' ))
dt2 <- data.table(id=c(1,1,1,1,1,1,2,2,2,2,3,3,3),
lat=c("NA","le","le","re","re","re","NA","re","NA","57", "57", "NA","bilat"),
outcome = c(0,0,1,1,1,1,0,0,0,0,0,0,1),
date= dates2, year= c(15,19,19,11,15,08,15,12,15,08,14,14,14))
我尝试了类似的方法，但它在原始集合中不起作用，因为我在开始日期之前得到了结果，所以我假设代码可能在这个小数据集中工作，但实际上，它在某种程度上是不正确的。
#left join dt1 and dt2
dt1_dt2 <- left_join( dt2,dt1, by= "id", suffix=c("2event","1op"))
#filter does with outcome after date1
dt1_dt2$tdiff = difftime(dt1_dt2$date2event,dt1_dt2$date1op, units= "days")
dt1_dt2 = dt1_dt2 %>% filter(outcome== 1) %>%
filter(tdiff <= 365, tdiff >= 0)
#then match on the closest date since farthest was not supported
setDT(dt1)
setDT(dt1_dt2)
setkey(dt1, id, lat) #key set to match
dt3 <- dt1_dt2[, date2, by =.(id, lat2), roll ="nearest"] #how can I keep all variables?
dt3 = unique(dt3, by = c("id", "date2","lat2"))
2 个解决方案
解决方案1
1 2021-02-20 06:55:18
更新的答案
# construct complete data
da <- merge(dt1,dt2,by=c("id","lat"),all.x = TRUE,suffixes = c("_start","_end"))
# select desired columns => add tdiff ==> replace outcome == NA with 0
da2 <- da[,.(id,lat,year_start,status,date_start,outcome,date_end)][
, tdiff := as.numeric( difftime(date_end, date_start, units= "days"))][, outcome:=fifelse(is.na(outcome),0,outcome)]
# add flag to show whether the part of da2 (id,lat) also appears in dt2
setkey(da2,id,lat)
setkey(dt2,id,lat)
da2[,flag:=FALSE][dt2,flag:=TRUE]
# get desired result
dt_desired <- da2[0 <= tdiff & tdiff <= 365 | lat == "NA" | is.na(date_end)]
rows <- dt_desired[flag==FALSE & outcome == 0]
# fill with last event's date_end within one year
dt_desired[flag==FALSE & outcome == 0]$date_end <- dt2[,.SD,keyby=.(id,date)][,.SD[.N],by=id][rows,date]
dt_desired[as.numeric( difftime(date_end, date_start, units= "days")) > 365]$date_end <- NA
结果：
id lat year_start status date_start outcome date_end tdiff flag
1: 1 le 18 1 2018-07-06 1 2019-04-03 271 TRUE
2: 1 re 11 1 2011-04-12 1 2011-07-14 93 TRUE
3: 2 le 15 0 2015-01-10 0 2015-11-10 NA FALSE
4: 2 re 11 0 2011-07-20 0 2012-04-23 278 TRUE
5: 3 57 13 0 2013-09-26 1 2014-01-15 111 TRUE
6: 3 NA 10 1 2010-02-18 0 <NA> NA FALSE
原始答案
根据您的代码，我得到的结果接近您想要的结果。 请检查是否正确。
dt1_dt2 <- left_join( dt2,dt1, by= "id", suffix=c("2event","1op"))
# add column tdiff, equal to your method
dt1_dt2[, tdiff := as.numeric( difftime(date2event, date1op, units= "days") )]
# select desired columns
dt1_dt2[0 <= tdiff & tdiff <= 365,
.(id,lat1op,year1op,status,date1op,outcome,date2event)]
我的结果与您的结果之间的差异位于第 5 行。 根据您提供的数据，我找不到任何带有NA的end_date 。 至于prior_outcome ，您没有展示如何计算它。 我认为这不是主要问题。
解决方案2
1 2021-02-22 02:10:47
这是使用非 equi 连接的选项：
cols <- c("outcome", "end_date")
dt1[, oneyr := date + 365L] #or in case of leap year, dt1[, oneyr := as.Date(sapply(date, function(d) seq(d, by="1 year", length.out=2L)[[2L]]), origin="1970-01-01")]
dt1[, (cols) :=
dt2[.SD, on=.(id, lat, date>=date, date<=oneyr), mult="first", .(x.outcome, x.date)]
]
dt1[is.na(outcome), (cols) :=
dt2[.SD, on=.(id, date>=date, date<=oneyr), mult="first", .(x.outcome, x.date)]
]
dt1[is.na(outcome), outcome := 0L]
output：
id lat year status date oneyr outcome end_date
1: 1 le 18 1 2018-07-06 2019-07-06 1 2019-04-03
2: 1 re 11 1 2011-04-12 2012-04-11 1 2011-07-14
3: 2 le 15 0 2015-01-10 2016-01-10 0 2015-11-10
4: 2 re 11 0 2011-07-20 2012-07-19 0 2012-04-23
5: 3 NA 10 1 2010-02-18 2011-02-18 0 <NA>
6: 3 57 13 0 2013-09-26 2014-09-26 1 2014-01-15
qn 更新后编辑。 不清楚新的所需 output 是什么，您可以尝试以下操作：
dt1[, oneyr := date + 365L]
cols <- paste0("i.", names(dt1))
a1 <- dt2[dt1, on=.(id, lat, date>=date, date<=oneyr), c(mget(cols),
.(outcome=outcome, end_date=x.date))]
setnames(a1, names(a1), gsub("^i.","",names(a1)))
a2 <- dt2[a1[is.na(outcome)], on=.(id, date>=date, date<=oneyr), c(mget(cols),
.(outcome=outcome, end_date=x.date))]
setnames(a2, names(a2), gsub("^i.","",names(a2)))
setorder(rbindlist(list(a1[!is.na(outcome)], a2), use.names=TRUE), id, date)[]
output：
id lat year status date oneyr outcome end_date
1: 1 re 11 1 2011-04-12 2012-04-11 1 2011-07-14
2: 1 le 18 1 2018-07-06 2019-07-06 0 2019-04-03
3: 1 le 18 1 2018-07-06 2019-07-06 1 2019-04-30
4: 2 re 11 0 2011-07-20 2012-07-19 0 2012-04-23
5: 2 le 15 0 2015-01-10 2016-01-10 0 2015-11-10
6: 2 le 15 0 2015-01-10 2016-01-10 0 2015-02-18
7: 3 NA 10 1 2010-02-18 2011-02-18 NA <NA>
8: 3 57 13 0 2013-09-26 2014-09-26 0 2014-01-15
在所需的 output 更新后编辑：
cols <- c("outcome", "end_date")
dt1[, oneyr := date + 365L] #or in case of leap year, dt1[, oneyr := as.Date(sapply(date, function(d) seq(d, by="1 year", length.out=2L)[[2L]]), origin="1970-01-01")]
dt1[, (cols) :=
dt2[.SD, on=.(id, lat, date>=date, date<=oneyr), by=.EACHI, {
w <- which(outcome==1L)
if (length(w) > 0L) {
.(outcome=outcome[w[1L]], x.date[w[1L]])
} else {
.(outcome=outcome[1L], x.date[1L])
}
}][, (1L:4L) := NULL]
]
dt1[is.na(outcome), (cols) :=
dt2[.SD, on=.(id, date>=date, date<=oneyr), by=.EACHI, {
w <- which(outcome==1L)
if (length(w) > 0L) {
.(outcome=outcome[w[1L]], x.date[w[1L]])
} else {
.(outcome=outcome[1L], x.date[1L])
}
}][, (1L:3L) := NULL]
]
dt1[is.na(outcome), outcome := 0L][]
output：
id lat year status date oneyr outcome end_date
1: 1 le 18 1 2018-07-06 2019-07-06 1 2019-04-30
2: 1 re 11 1 2011-04-12 2012-04-11 1 2011-07-14
3: 2 le 15 0 2015-01-10 2016-01-10 0 2015-02-18
4: 2 re 11 0 2011-07-20 2012-07-19 0 2012-04-23
5: 3 NA 10 1 2010-02-18 2011-02-18 0 <NA>
6: 3 bilat 13 1 2013-09-26 2014-09-26 1 2014-02-28
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