我需要每隔 5 分钟对我的刻度数据集进行先前的刻度聚合。请注意，我想做的类似于高频包中的 aggregateTrades() 函数。但是由于其他一些数据处理问题，我需要在不使用高频包的情况下解决这个问题。这是我的数据集：
dput(tt)
structure(c(1371.25, NA, 1373.95, NA, NA, 1373, NA, 1373.95,
1373.9, NA, NA, 1374, 1374.15, NA, 1374, 1373.85, 1372.55, 1374.05,
1374.15, 1374.75, NA, NA, 1375.9, 1374.05, NA, NA, NA, NA, NA,
NA, NA, 1375, NA, NA, NA, NA, NA, 1376.35, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 1376.25, NA, 1378, 1376.5, NA, NA, NA, 1378,
1378, NA, NA, 1378.8, 231.9, 231.85, NA, 231.9, 231.85, 231.9,
231.8, 231.9, 232.6, 231.95, 232.35, 232, 232.1, 232.05, 232.05,
232.05, 231.5, 231.3, NA, NA, 231.1, 231.1, 231.1, 231, 231,
230.95, 230.6, 230.6, 230.7, 230.6, 231, NA, 231, 231, 231.45,
231.65, 231.4, 231.7, 231.3, 231.25, 231.25, 231.4, 231.4, 231.85,
231.75, 231.5, 231.55, 231.35, NA, 231.5, 231.5, NA, 231.5, 231.25,
231.15, 231, 231, 231, 231.05, NA), .indexCLASS = c("POSIXct",
"POSIXt"), tclass = c("POSIXct", "POSIXt"), .indexTZ = "Asia/Calcutta", tzone = "Asia/Calcutta", index = structure(c(1459481850,
1459482301, 1459482302, 1459482303, 1459482304, 1459482305, 1459482306,
1459482307, 1459482309, 1459482310, 1459482311, 1459482312, 1459482314,
1459482315, 1459482316, 1459482317, 1459482318, 1459482319, 1459482320,
1459482321, 1459482322, 1459482323, 1459482324, 1459482326, 1459482328,
1459482329, 1459482330, 1459482331, 1459482332, 1459482336, 1459482337,
1459482338, 1459482339, 1459482342, 1459482344, 1459482346, 1459482347,
1459482348, 1459482349, 1459482350, 1459482351, 1459482354, 1459482355,
1459482356, 1459482357, 1459482358, 1459482359, 1459482362, 1459482363,
1459482364, 1459482369, 1459482370, 1459482371, 1459482372, 1459482373,
1459482378, 1459482379, 1459482380, 1459482382, 1459482388), tzone = "Asia/Calcutta", tclass = c("POSIXct",
"POSIXt")), .Dim = c(60L, 2L), .Dimnames = list(NULL, c("A",
"B")), class = c("xts", "zoo"))
这是我之前的刻度聚合代码：
ag.5min.tt<-tt%>%filter(as.Date(index(tt)))%>%lapply(aggregate(by=cut(format(index(tt), format = "%H:%M:%S"), breaks = "5 mins", Fun=tail)))
我试图用上面的代码做的是每天为 A 和 B 的价格设置 5 分钟的间隔。但我得到了错误。请建议如何解决此错误：
Error in UseMethod("filter_") :
no applicable method for 'filter_' applied to an object of class "c('xts', 'zoo')"
谢谢。
编辑： 将 xts 对象转换为数据框：
tt<-as.data.frame(tt)
tt<-data.frame(Time=rownames(tt), coredata(tt))
ag.5min.tt<-tt%>% filter(as.Date(index(tt)))%>%lapply(aggregate(by=cut(format(index(tt), format = "%H:%M:%S"), breaks = "5 mins", Fun=tail)))
新错误：
Error in eval(substitute(expr), envir, enclos) :
filter condition does not evaluate to a logical vector.
编辑：尝试：
tt$Time<- as.POSIXct(tt$Time, format="%Y-%m-%d %H:%M:%S")
ag.5min.tt<-tt%>% group_by(Time==as.Date(tt$Time))%>%lapply(aggregate(by=cut(format(tt$Time, format = "%H:%M:%S"), breaks = "5 mins", Fun=tail)))
错误：
Error in cut.default(format(tt$Time, format = "%H:%M:%S"), breaks = "5 mins", :
'x' must be numeric
In addition: Warning message:
In eval(substitute(expr), envir, enclos) :
Incompatible methods ("Ops.POSIXt", "Ops.Date") for "=="
结果看起来像这样。每五分钟时间戳将具有该特定时间戳的值，或者如果存在 NA，则该时间戳将具有股票 A 和 B 的最后一个非 NA 值
time A B
1 2016-04-01 09:00:00 NA NA
2 2016-04-01 09:05:00 NA NA
3 2016-04-01 09:10:00 NA NA
4 2016-04-01 09:15:00 1371.25 231.90
5 2016-04-01 09:20:00 1376.35 231.55