我有两个数据表,我们称它们为权重
和值
。
weights
表有 5 列,如下所示:
first POSIXct
late POSIXct
nodeid integer
aggid integer
weight numeric
values
表包含以下列
nodeid integer
Date POSIXct
hour integer
value decimal
这个想法是生成一个新表,在该表中它将根据权重将节点的加权平均值放入聚合节点中。然而,权重会随着时间的推移而变化,需要根据最早和最晚的日期进行匹配。执行此操作的 SQL 语法如下所示
select v.Date, v.hour, w.aggid, sum(v.value*w.weight) as aggvalue
from values v inner join weights w
on v.nodeid=w.nodeid and v.date between w.first and w.late
group by aggid, date, hour
考虑到 SQL 语法中的 Between
逻辑,我不太确定从哪里开始。这在 data.table 语法中是否可行,或者我是否需要将 weights
表转换为每天都有一行而不是使用范围?
这是一些示例数据(抱歉太长了)...
values<-data.table(nodeid = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,
6L, 6L, 6L, 6L, 6L), Date = c("2013-07-02", "2013-07-02", "2013-07-05",
"2013-07-08", "2013-07-10", "2013-07-02", "2013-07-02", "2013-07-05",
"2013-07-08", "2013-07-10", "2013-07-02", "2013-07-02", "2013-07-05",
"2013-07-08", "2013-07-10", "2013-07-02", "2013-07-02", "2013-07-05",
"2013-07-08", "2013-07-10", "2013-07-02", "2013-07-02", "2013-07-05",
"2013-07-08", "2013-07-10", "2013-07-02", "2013-07-02", "2013-07-05",
"2013-07-08", "2013-07-10"), hour = c(1L, 2L, 23L, 2L, 2L, 1L,
2L, 23L, 2L, 2L, 1L, 2L, 23L, 2L, 2L, 1L, 2L, 23L, 2L, 2L, 1L,
2L, 23L, 2L, 2L, 1L, 2L, 23L, 2L, 2L), value = c(8.234, 3.218,
0.787, 8.689, 6.218, 6.89, 1.914, 2.459, 6.683, 8.122, 0.281,
1.136, 1.993, 7.27, 9.582, 5.777, 1.375, 9.204, 7.862, 0.633,
2.433, 1.842, 7.178, 10.692, 1.417, 1.259, 2.619, 0.031, 6.744,
5.941))
weights<-data.table(first = c("2013-07-01", "2013-07-01", "2013-07-01",
"2013-07-01", "2013-07-01", "2013-07-01", "2013-07-08", "2013-07-08",
"2013-07-08", "2013-07-08", "2013-07-08", "2013-07-08"), late = c("2013-07-07",
"2013-07-07", "2013-07-07", "2013-07-07", "2013-07-07", "2013-07-07",
"2013-07-20", "2013-07-20", "2013-07-20", "2013-07-20", "2013-07-20",
"2013-07-20"), nodeid = c(1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L), aggid = c(1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L), weight = c(0.5, 0.25, 0.25, 0.3, 0.5, 0.2, 0.6, 0.2,
0.2, 0.4, 0.45, 0.15))
exresults<-data.table(aggid = c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L), Date = c("2013-07-02", "2013-07-02", "2013-07-02", "2013-07-02",
"2013-07-05", "2013-07-05", "2013-07-08", "2013-07-08", "2013-07-10",
"2013-07-10"), hour = c(1L, 1L, 2L, 2L, 23L, 23L, 2L, 2L, 2L,
2L), aggvalue = c(5.90975, 3.2014, 2.3715, 1.8573, 1.5065, 6.3564,
8.004, 8.9678, 7.2716, 1.782))
最佳答案
使用data.table
连接的roll
参数:
setkey(values, nodeid, Date)
setkey(weights, nodeid, late)
weights[values, roll = -Inf][, list(aggvalue = sum(weight*value)),
by = list(aggid, Date = late, hour)]
# aggid Date hour aggvalue
# 1: 1 2013-07-02 1 5.90975
# 2: 1 2013-07-02 2 2.37150
# 3: 1 2013-07-05 23 1.50650
# 4: 1 2013-07-08 2 8.00400
# 5: 1 2013-07-10 2 7.27160
# 6: 2 2013-07-02 1 3.20140
# 7: 2 2013-07-02 2 1.85730
# 8: 2 2013-07-05 23 6.35640
# 9: 2 2013-07-08 2 8.96780
#10: 2 2013-07-10 2 1.78200
注意:如果正确的范围不存在,我会小心 - 我没有测试这种边缘情况。
关于r - data.table 连接使用一个表中的两列和另一表中的一列,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/17867553/