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我正在编写一个给定路径的函数，它将找到文件夹中的所有文件，并将所有 csv 读入一个 xts 对象。这些文件都有相同的日期，我希望每个文件成为 xts 中的另一列。我得到了以下函数，但在 temp[, 1] 中出现错误：维数不正确。我究竟做错了什么？

make.libor.xts <- function(folder){
  filenames <- list.files(path=folder, full.names=TRUE)
  tables <- lapply(filenames, function(x){as.xts(read.zoo(x, sep=",", format="%Y-%m-%d", header=TRUE))})
  cnames <- lapply(filenames, function(x){basename(x)})
  myxts <- tables[1]
  names(myxts) <- cnames[1]
  if(length(filenames)>1){
    for(i in 2:length(filenames)){
      temp <- tables[i]
      myxts$cnames[i] <- temp[,1]
    }
  }
  return(myxts)
}
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1 回答 1

1

您的代码可以简化如下。使用Reduce函数调用merge.xtsxts 对象列表。

dir("temp")
## [1] "AAPL.csv" "IBM.csv"  "MSFT.csv"


READ.ALL.XTS <- function(folder) {
    filenames <- list.files(path = folder, full.names = TRUE)
    tables <- lapply(filenames, function(x) {
        as.xts(read.zoo(x, sep = ",", format = "%Y-%m-%d", header = TRUE))
    })

    # Lets see contents of tables
    cat("Calling from inside function begin...\n")
    print(head(tables[[1]]))
    print(head(tables[[2]]))
    print(head(tables[[3]]))
    cat("Calling from inside function end...\n")
    cnames <- sapply(filenames, function(x) {
        basename(x)
    })
    combinedxts <- Reduce(f = merge.xts, tables)
    names(combinedxts) <- cnames
    return(combinedxts)
}

result <- READ.ALL.XTS("temp")
## Calling from inside function begin...
##              [,1]
## 2013-01-03 542.10
## 2013-01-04 527.00
## 2013-01-07 523.90
## 2013-01-08 525.31
## 2013-01-09 517.10
## 2013-01-10 523.51
##              [,1]
## 2013-01-03 195.27
## 2013-01-04 193.99
## 2013-01-07 193.14
## 2013-01-08 192.87
## 2013-01-09 192.32
## 2013-01-10 192.88
##             [,1]
## 2013-01-03 27.25
## 2013-01-04 26.74
## 2013-01-07 26.69
## 2013-01-08 26.55
## 2013-01-09 26.70
## 2013-01-10 26.46
## Calling from inside function end...


head(result)
##            AAPL.csv IBM.csv MSFT.csv
## 2013-01-03   542.10  195.27    27.25
## 2013-01-04   527.00  193.99    26.74
## 2013-01-07   523.90  193.14    26.69
## 2013-01-08   525.31  192.87    26.55
## 2013-01-09   517.10  192.32    26.70
## 2013-01-10   523.51  192.88    26.46
于 2013-04-16T08:39:02.893 回答