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我有格式的时间序列数据

                        Ask    Bid  Trade Ask_Size Bid_Size Trade_Size
2016-11-01 01:00:03     NA 938.10     NA       NA      203         NA
2016-11-01 01:00:04     NA 937.20     NA       NA      100         NA
2016-11-01 01:00:04 938.00     NA     NA       28       NA         NA
2016-11-01 01:00:04     NA 938.10     NA       NA      203         NA
2016-11-01 01:00:04 939.00     NA     NA       11       NA         NA
2016-11-01 01:00:05     NA 938.15     NA       NA       19         NA
2016-11-01 01:00:06     NA 937.20     NA       NA      100         NA
2016-11-01 01:00:06 938.00     NA     NA       28       NA         NA
2016-11-01 01:00:06     NA     NA 938.10       NA       NA         69
2016-11-01 01:00:06     NA     NA 938.10       NA       NA        831
2016-11-01 01:00:06     NA 938.10     NA       NA      134         NA

时间序列数据的结构是

str(df_ts)

An ‘xts’ object on 2016-11-01 01:00:03/2016-11-02 12:59:37 containing:
  Data: num [1:35797, 1:6] NA NA 938 NA 939 NA NA 938 NA NA ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr [1:6] "Ask" "Bid" "Trade" "Ask_Size" ...
  Indexed by objects of class: [POSIXct,POSIXt] TZ: 
  xts Attributes:  
 NULL

如何创建 5 分钟的时间序列数据的子集。开始时间和结束时间将由用户定义

样本数据可以在

https://www.dropbox.com/s/m94y6pbhjlkny1l/Sample_HFT.csv?dl=0

请帮忙

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1 回答 1

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您可以使用 lubridate 和 apply 函数。我假设您的时间戳（日期和时间）位于第一列，并且我将该列命名为“时间戳”。数据框是df。首先安装 lubridate 包。结果将存储在不同的数据帧 df2 中。

library(lubridate)

# Round to 5 minutes
df$timestamp <- ceiling_date(as.POSIXct(df$timestamp), unit = "5 minutes")

# Create data frame to store results
df2 <- NULL
df2$timestamp <- levels(factor(df$timestamp))
df2 <- apply(df[,2:ncol(df)], 2, function(x)
             {
              df2 <<- cbind(df2, aggregate(x ~ df$timestamp, FUN = sum)[2])[[ncol(df)-2]]
             })
names(df2) <- names(df)
于 2016-11-26T04:15:27.297 回答