计算转换为OHLC时的滴答数

I have an xts object in R, myticks_xts, which consists of tick data from a financial security and looks as below:

我在R中有一个xts对象myticks_xts，它包含来自财务安全的tick数据，如下所示：

myticks_xts[1:10,]
                         V3      V4            V5
2014-01-01 21:55:34.378 1.37622 1.37693 1.37666900000
2014-01-01 21:55:40.410 1.37624 1.37698 1.37673727273
2014-01-01 21:55:47.210 1.37619 1.37696 1.37673702703
2014-01-01 21:55:57.963 1.37616 1.37696 1.37673702703
2014-01-01 21:56:03.117 1.37616 1.37694 1.37670529412
2014-01-01 21:56:07.253 1.37616 1.37692 1.37665407407
2014-01-01 21:56:16.911 1.37620 1.37695 1.37673411765
2014-01-01 21:56:19.433 1.37615 1.37692 1.37665407407
2014-01-01 21:56:24.970 1.37615 1.37691 1.37668466667
2014-01-01 21:56:24.971 1.37615 1.37689 1.37667203390

I can convert this tick data into 10 second bars (OHLC data) by using:

我可以使用以下方法将此刻度数据转换为10秒柱（OHLC数据）：

to.period(myticks_xts,'seconds',10)

I would however like to have an extra column representing 'Volume' which counts the number of ticks inside each bar. For example in the above, the bar 21:55:30-21:55:40 would have 1 tick, the bar 21:55:40-21:55:50 would have 2 ticks, and so on. Is there a simple way to do this?

但是我希望有一个额外的列代表'Volume'，它会计算每个柱内的刻度数。例如，在上面，条形码21：55：30-21：55：40将有1个刻度，条形图21：55：40-21：55：50将有2个刻度，依此类推。有一个简单的方法吗？

1 个解决方案

#1

The easiest way is to create a column called Volume. Then to.period will magically do it for you.

最简单的方法是创建一个名为Volume的列。然后to.period会神奇地为你做。

x <- cbind(myticks_xts$V5, Volume=1)
to.period(x, "seconds", 10)
#                             x.Open      x.High       x.Low     x.Close x.Volume
#2014-01-01 21:55:34.378 1.376669000 1.376669000 1.376669000 1.376669000        1
#2014-01-01 21:55:47.210 1.376737273 1.376737273 1.376737027 1.376737027        2
#2014-01-01 21:55:57.963 1.376737027 1.376737027 1.376737027 1.376737027        1
#2014-01-01 21:56:07.253 1.376705294 1.376705294 1.376654074 1.376654074        2
#2014-01-01 21:56:19.433 1.376734118 1.376734118 1.376654074 1.376654074        2
#2014-01-01 21:56:24.970 1.376684667 1.376684667 1.376672034 1.376672034        2

Otherwise, you'd need to use period.apply

否则，您需要使用period.apply

#1