R：将 xts 对象列表转换为 data.frame答案

【问题标题】：R: Convert list of xts objects to data.frameR：将 xts 对象列表转换为 data.frame
【发布时间】：2014-05-17 19:14:36
【问题描述】：

我有一个 xts 对象列表（几个国家/地区的年度时间序列）。现在，我想将整个列表转换为单个数据框以运行面板数据回归。我认为有一种简单的方法可以让我为每个 list 对象（xts 时间序列）和 时间信息 使用 name > 对于每个 xts 对象 作为变量，共同唯一标识每个面板数据观察。

我希望我已经足够清楚地说明了这个问题。这是我目前所拥有的：

library(data.table)
lstData <- Map(as.data.frame, data)
Data <- rbindlist(lstData)

不幸的是，这个简单的转换不允许我将国家标识符和时间序列信息保留为标识符，如果我想进行面板数据分析，渲染是无用的。

【问题讨论】：

标签： r panel xts

【解决方案1】：

我会试试这个（尽管ldply 解决方案可能更快）。

library(xts)
A <- xts(read.zoo(data.frame(day=as.Date("2001-05-25") + 1:10, x=rnorm(10), y=rnorm(10))))
B <- xts(read.zoo(data.frame(day=as.Date("2001-05-25") + 1:10, x=rnorm(10), y=rnorm(10))))
C <- list(US=A, CAN=B)
D <- do.call(merge.zoo, C)
E <- data.frame(day=index(D), coredata(D))
reshape(E, direction="long", idvar="day", timevar="country", varying=2:ncol(E))

产量：

> reshape(E, direction="long", idvar="day", timevar="country", varying=2:ncol(E))
                      day country           x           y
2001-05-26.US  2001-05-26      US -1.14792688 -0.70425857
2001-05-27.US  2001-05-27      US  0.42892010 -0.62678907
2001-05-28.US  2001-05-28      US  1.20302730 -0.88504965
2001-05-29.US  2001-05-29      US  0.14411623  0.62155740
2001-05-30.US  2001-05-30      US -0.30979083 -1.63573976
2001-05-31.US  2001-05-31      US -0.53765221 -0.94028377
2001-06-01.US  2001-06-01      US  0.21273968  0.39703515
2001-06-02.US  2001-06-02      US -0.45567642  0.28003478
2001-06-03.US  2001-06-03      US -0.52659903 -1.05184085
2001-06-04.US  2001-06-04      US  0.23540896 -1.52234888
2001-05-26.CAN 2001-05-26     CAN  0.27341723 -0.29382874
2001-05-27.CAN 2001-05-27     CAN  0.08398618  0.88950783
2001-05-28.CAN 2001-05-28     CAN  0.24333694  0.60005146
2001-05-29.CAN 2001-05-29     CAN  0.82480254 -0.77898367
2001-05-30.CAN 2001-05-30     CAN -0.18744699 -1.14777217
2001-05-31.CAN 2001-05-31     CAN  0.98918900 -0.04893292
2001-06-01.CAN 2001-06-01     CAN -0.27379800 -1.23558134
2001-06-02.CAN 2001-06-02     CAN -0.88556293  2.34522201
2001-06-03.CAN 2001-06-03     CAN -0.68985258 -0.37681843
2001-06-04.CAN 2001-06-04     CAN  0.11916878 -2.39336976

【讨论】：

【解决方案2】：

library(xts)
library(plyr)

# make up the data since none proived

data(sample_matrix)
data <- list(country1=as.xts(sample_matrix, descr='my new xts object'),
             country2=as.xts(sample_matrix, descr='my new xts object'),
             country3=as.xts(sample_matrix, descr='my new xts object'),
             country4=as.xts(sample_matrix, descr='my new xts object'))


Data <- ldply(data)

# examine new data frame

str(Data)
'data.frame':   720 obs. of  5 variables:
 $ .id  : chr  "country1" "country1" "country1" "country1" ...
 $ Open : num  50 50.2 50.4 50.4 50.2 ...
 $ High : num  50.1 50.4 50.4 50.4 50.2 ...
 $ Low  : num  50 50.2 50.3 50.2 50.1 ...
 $ Close: num  50.1 50.4 50.3 50.3 50.2 ...

head(Data)
       .id     Open     High      Low    Close
1 country1 50.03978 50.11778 49.95041 50.11778
2 country1 50.23050 50.42188 50.23050 50.39767
3 country1 50.42096 50.42096 50.26414 50.33236
4 country1 50.37347 50.37347 50.22103 50.33459
5 country1 50.24433 50.24433 50.11121 50.18112
6 country1 50.13211 50.21561 49.99185 49.99185

tail(Data)
         .id     Open     High      Low    Close
715 country4 47.20471 47.42772 47.13405 47.42772
716 country4 47.44300 47.61611 47.44300 47.61611
717 country4 47.62323 47.71673 47.60015 47.62769
718 country4 47.67604 47.70460 47.57241 47.60716
719 country4 47.63629 47.77563 47.61733 47.66471
720 country4 47.67468 47.94127 47.67468 47.76719

【讨论】：