Question

我有这种格式的数据

> data = data.table(id = 1:10, date = seq(as.Date("2016-01-01"), by = 1, length = 10))
> data
    id       date
 1:  1 2016-01-01
 2:  2 2016-01-02
 3:  3 2016-01-03
 4:  4 2016-01-04
 5:  5 2016-01-05
 6:  6 2016-01-06
 7:  7 2016-01-07
 8:  8 2016-01-08
 9:  9 2016-01-09
10: 10 2016-01-10

我有另一个矩阵，它是我希望预先形成的查询/子集。

> query = data.table(id = c(1,4,7), date_start = c("2016-01-01", "2016-01-01", "2016-01-01"), date_end = c("2016-01-04", "2016-01-02", "2016-01-03"))
> query
   id date_start   date_end
1:  1 2016-01-01 2016-01-04
2:  4 2016-01-01 2016-01-02
3:  7 2016-01-01 2016-01-03

我希望做这样的事情：

subset(data, (id == query[1] & date > date_start[1] & date < date_end[1]) | 
       (id == query[2] & date > date_start[2] & date < date_end[2]) |
       (id == query[3] & date > date_start[3] & date < date_end[3]))

是否自动生成子集查询而不使用for-loop并对结果进行rbinding。

由于

Answer 1

如果我们稍微改变OP的数据

library(data.table)
data = setDT(structure(list(id = 1:10, date = structure(16801:16810, class = c("IDate", 
"Date")), date2 = structure(16801:16810, class = c("IDate", "Date"
))), .Names = c("id", "date", "date2"), row.names = c(NA, -10L
), class = c("data.table", "data.frame"), sorted = c("id", 
"date", "date2")))

query = setDT(structure(list(id = c(1, 4, 7), date_start = 
structure(c(16801L, 
16801L, 16801L), class = c("IDate", "Date")), date_end = structure(c(16804L, 
16802L, 16803L), class = c("IDate", "Date"))), .Names = c("id", 
"date_start", "date_end"), row.names = c(NA, -3L), class = c("data.table", 
"data.frame"), sorted = c("id", 
"date_start", "date_end")))

...然后我们可以使用foverlaps之类的

foverlaps(data, query, nomatch=0)
#    id date_start   date_end       date      date2
# 1:  1 2016-01-01 2016-01-04 2016-01-01 2016-01-01

对于这种方法，我认为在合并之前需要采取这些步骤：

所有日期均为IDate s
在主数据
在每张桌子上设置密钥

Answer 2

在current development version中，您可以按如下方式直接执行non-equi加入：

# data.table v1.9.7+
data[query, .(id, x.date), on=.(id, date>=date_start, date<=date_end)]

如有必要，添加nomatch=0L以删除结果中不匹配的行。

目前需要.(id, x.date)，直到我训练非等连接的默认输出应如何。

Answer 3

require(data.table)
data = data.table(id = 1:10, date = seq(as.Date("2016-01-01"), by = 1, length = 10))
query = data.table(id = c(1,4,7), date_start = c("2016-01-01", "2016-01-01", 
"2016-01-01"), date_end = c("2016-01-04", "2016-01-02", "2016-01-03"))

首先你可以加入他们：

data.full <- merge(data,query,by="id", all.x=T)

接下来，如果您要排除query中未引用的观察值并保留那些在日期范围内被引用的观察值，那么您可以这样做：

data.final <- data.full[date >= date_start & date <= date_end,]

data.final
   id       date date_start   date_end
1:  1 2016-01-01 2016-01-01 2016-01-04

或者如果你想保留query中没有引用的记录，并保留那些在日期范围内被引用的记录：

data.final <- data.full[is.na(date_start) | (date >= date_start & date <= date_end),]
data.final
   id       date date_start   date_end
1:  1 2016-01-01 2016-01-01 2016-01-04
2:  2 2016-01-02         NA         NA
3:  3 2016-01-03         NA         NA
4:  5 2016-01-05         NA         NA
5:  6 2016-01-06         NA         NA
6:  8 2016-01-08         NA         NA
7:  9 2016-01-09         NA         NA
8: 10 2016-01-10         NA         NA

有效地多次分组data.table

3 个答案: