RBbg - 重塑时间序列数据

时间:2013-12-01 00:08:24

标签: r time-series reshape

有没有更好的方法来重塑数据帧数据?

temp <- bdh(conn,c("AUDUSD Curncy","EURUSD Curncy"),"PX_LAST","20110101")

给出

head(temp)
         ticker       date PX_LAST
1 AUDUSD Curncy 2011-01-01      NA
2 AUDUSD Curncy 2011-01-02      NA
3 AUDUSD Curncy 2011-01-03  1.0205
4 AUDUSD Curncy 2011-01-04  1.0040
5 AUDUSD Curncy 2011-01-05  1.0014
6 AUDUSD Curncy 2011-01-06  0.9969

tail(temp)
            ticker       date PX_LAST
2127 EURUSD Curncy 2013-11-26  1.3557
2128 EURUSD Curncy 2013-11-27  1.3570
2129 EURUSD Curncy 2013-11-28  1.3596
2130 EURUSD Curncy 2013-11-29  1.3591
2131 EURUSD Curncy 2013-11-30      NA
2132 EURUSD Curncy 2013-12-01      NA
换句话说,数据只是相互垂直固定,需要进一步处理才能使它们正常工作。如何将这些数据重新组合成各种代码,即

head(temp)
           AUDUSD.Curncy EURUSD.Curncy
2011-01-01            NA            NA
2011-01-02            NA            NA
2011-01-03        1.0205        1.3375
2011-01-04        1.0040        1.3315
2011-01-05        1.0014        1.3183
2011-01-06        0.9969        1.3028

我用谷歌搜索的所有重塑问题都没有我想要的那种重塑。我已经实现了下面给出的自己的零碎解决方案,但为了学习,我想问你们,如果有一个更优雅的解决方案吗?

3 个答案:

答案 0 :(得分:5)

您可以尝试read.zoo。使用index.column指定存储列索引/时间,并根据split columnn重新整形数据。结果是zoo时间序列

library(zoo)

z <- read.zoo(text = "ticker     date PX_LAST
1 AUDUSD 2011-01-01      NA
2 AUDUSD  2011-01-02      NA
3 AUDUSD 2011-01-03  1.0205
4 AUDUSD 2011-01-04  1.0040
5 AUDUSD  2011-01-05  1.0014
6 AUDUSD 2011-01-06  0.9969
2127 EURUSD  2013-11-26  1.3557
2128 EURUSD  2013-11-27  1.3570
2129 EURUSD  2013-11-28  1.3596
2130 EURUSD  2013-11-29  1.3591
2131 EURUSD  2013-11-30      NA
2132 EURUSD  2013-12-01      NA", index.column = "date", split = "ticker")

z
#            AUDUSD EURUSD
# 2011-01-01     NA     NA
# 2011-01-02     NA     NA
# 2011-01-03 1.0205     NA
# 2011-01-04 1.0040     NA
# 2011-01-05 1.0014     NA
# 2011-01-06 0.9969     NA
# 2013-11-26     NA 1.3557
# 2013-11-27     NA 1.3570
# 2013-11-28     NA 1.3596
# 2013-11-29     NA 1.3591
# 2013-11-30     NA     NA
# 2013-12-01     NA     NA

str(z)

答案 1 :(得分:1)

这正是我们创建RbbgExtension包的原因。它是Rbbg软件包的一个包装器,它在处理财务数据时处理许多问题 - 我们在日常工作中遇到的问题,包括金融机构的回溯交易策略等。

正如您所看到的输出是xts对象,但如果查询跨越多个代码和多个字段,那么输出将是一个数组 - 但您可以阅读文档中的原因。

我们已将软件包开源并在GitHub上公开发布。只需使用哈德利的开发工具&#39;函数install_github(&#34; pgarnry / RbbgExtension&#34;)获取包。它有一些依赖关系,包括&#34; Rbbg&#34;。

> require(RbbgExtension)
Loading required package: RbbgExtension
> 
> tickers <- c("AUDUSD", "EURUSD")
> 
> prices <- HistData(tickers = tickers,
+                    type = "Curncy",
+                    fields = "PX_LAST",
+                    startdate = "20110101")
R version 3.1.2 (2014-10-31) 
rJava Version 0.9-6 
Rbbg Version 0.5.3 
Java environment initialized successfully.
Looking for most recent blpapi3.jar file...
Adding C:\blp\API\APIv3\JavaAPI\v3.7.1.1\lib\blpapi3.jar to Java classpath
Bloomberg API Version 3.7.1.1 
> class(prices)
[1] "xts" "zoo"
> head(prices)
           AUDUSD EURUSD
2011-01-03 1.0168 1.3361
2011-01-04 1.0051 1.3308
2011-01-05 0.9995 1.3149
2011-01-06 0.9944 1.3003
2011-01-07 0.9959 1.2907
2011-01-10 0.9956 1.2951
> tail(prices)
           AUDUSD EURUSD
2015-01-26 0.7925 1.1238
2015-01-27 0.7937 1.1381
2015-01-28 0.7889 1.1287
2015-01-29 0.7762 1.1320
2015-01-30 0.7762 1.1291
2015-02-02 0.7806 1.1351

答案 2 :(得分:-1)

rbbg的blh(现在是bdh)是愚蠢的。这会正确输出时间序列。

bdhx <- function(conn,securities,start_date,end_date=NULL,fields="PX_LAST",override_fields = NULL,overrides = NULL) {
  temp <- bdh(conn=conn,securities=securities,fields=fields,start_date=start_date,end_date=end_date,override_fields=override_fields)
  if (colnames(temp)[1]=="date")
    {temp <- as.xts(temp)[,-1];colnames(temp) <- securities;res <- temp;}
  else
    {cn <- unique(temp[,1]);fil <- temp[,1]==cn[1];
     res <- xts(temp[fil,3],as.Date(temp[fil,2]));colnames(res) <- securities[1];
         for (i in 4:(length(cn)+2)){
          fil <- temp[,1]==cn[i-2]
          temp2 <- xts(temp[fil,3],as.Date(temp[fil,2]));colnames(temp2) <- securities[i-2];
          res <- merge.xts(res,temp2)}
     }
  res}