轉換data.frame到XTS order.by需要一個適當的基於時間的對象

我有這樣的下列數據幀：轉換data.frame到XTS order.by需要一個適當的基於時間的對象

> head(table,10) 
    Date  Open High Low Close Volume  Adj.Close 
1 2014-04-11 32.64 33.48 32.15 32.87 28040700  32.87 
2 2014-04-10 34.88 34.98 33.09 33.40 33970700  33.40 
3 2014-04-09 34.19 35.00 33.95 34.87 21597500  34.87 
4 2014-04-08 33.10 34.43 33.02 33.83 35440300  33.83 
5 2014-04-07 34.11 34.37 32.53 33.07 47770200  33.07 
6 2014-04-04 36.01 36.05 33.83 34.26 41049900  34.26 
7 2014-04-03 36.66 36.79 35.51 35.76 16792000  35.76 
8 2014-04-02 36.68 36.86 36.56 36.64 14522800  36.64 
9 2014-04-01 36.16 36.86 36.15 36.49 15734000  36.49 
10 2014-03-31 36.46 36.58 35.73 35.90 15153200  35.90

我試圖把它做成使用

> table3<-xts(table[,-1],order.by=table$Date)

一個XTS文件

但我得到這個錯誤：

Error in xts(table[, -1], order.by = table$Date) : 
    order.by requires an appropriate time-based object

我哪裏出錯了？我認爲表格$ Date是基於時間的。

來源

2014-04-22 asosnovsky

?xts說，以下有關order.by：

Currently acceptable classes include: ‘Date’, ‘POSIXct’, ‘timeDate’, as well as ‘yearmon’ and ‘yearqtr’ where the index values remain unique.

因此需要額外的顯式轉換，例如到POSIXct：

xts(table[, -1], order.by=as.POSIXct(table$Date)) 
      Open High Low Close Volume Adj.Close 
2014-03-31 36.46 36.58 35.73 35.90 15153200  35.90 
2014-04-01 36.16 36.86 36.15 36.49 15734000  36.49 
2014-04-02 36.68 36.86 36.56 36.64 14522800  36.64 
2014-04-03 36.66 36.79 35.51 35.76 16792000  35.76 
2014-04-04 36.01 36.05 33.83 34.26 41049900  34.26 
2014-04-07 34.11 34.37 32.53 33.07 47770200  33.07 
2014-04-08 33.10 34.43 33.02 33.83 35440300  33.83 
2014-04-09 34.19 35.00 33.95 34.87 21597500  34.87 
2014-04-10 34.88 34.98 33.09 33.40 33970700  33.40 
2014-04-11 32.64 33.48 32.15 32.87 28040700  32.87

另一種選擇：

xts(table[, -1], order.by=as.Date(table$Date))

來源

2014-04-23 07:46:09 tonytonov

完美的解決方案。在這個問題上工作了很長時間。 –

-1

使用tidyquant包的另一種方法是使用其中as_xts()是專爲數據幀轉換爲XTS對象。只需指定date_col作爲包含日期的列。如果日期列的類是字符，它將需要從字符轉換爲日期類mutate(date = ymd(date))或類似的東西。以下是如何使用as_xts()：

library(tidyquant) 
# Get stock prices 
stock_prices <- "AAPL" %>% 
    tq_get(get = "stock.prices", 
      from = "2007-01-01", 
      to = "2017-01-01") 
stock_prices 
#> # A tibble: 2,518 Ã— 7 
#>   date open high low close volume adjusted 
#>  <date> <dbl> <dbl> <dbl> <dbl>  <dbl> <dbl> 
#> 1 2007-01-03 86.29 86.58 81.90 83.80 309579900 10.85709 
#> 2 2007-01-04 84.05 85.95 83.82 85.66 211815100 11.09807 
#> 3 2007-01-05 85.77 86.20 84.40 85.05 208685400 11.01904 
#> 4 2007-01-08 85.96 86.53 85.28 85.47 199276700 11.07345 
#> 5 2007-01-09 86.45 92.98 85.15 92.57 837324600 11.99333 
#> 6 2007-01-10 94.75 97.80 93.45 97.00 738220000 12.56728 
#> 7 2007-01-11 95.94 96.78 95.10 95.80 360063200 12.41180 
#> 8 2007-01-12 94.59 95.06 93.23 94.62 328172600 12.25892 
#> 9 2007-01-16 95.68 97.25 95.45 97.10 311019100 12.58023 
#> 10 2007-01-17 97.56 97.60 94.82 94.95 411565000 12.30168 
#> # ... with 2,508 more rows 

# Coerce to xts object 
stock_prices %>% 
    as_xts(date_col = date) 
#>    open high low close volume adjusted 
#> 2007-01-03 86.29 86.58 81.90 83.80 309579900 10.85709 
#> 2007-01-04 84.05 85.95 83.82 85.66 211815100 11.09807 
#> 2007-01-05 85.77 86.20 84.40 85.05 208685400 11.01904 
#> 2007-01-08 85.96 86.53 85.28 85.47 199276700 11.07345 
#> 2007-01-09 86.45 92.98 85.15 92.57 837324600 11.99333 
#> 2007-01-10 94.75 97.80 93.45 97.00 738220000 12.56728 
#> 2007-01-11 95.94 96.78 95.10 95.80 360063200 12.41180 
#> 2007-01-12 94.59 95.06 93.23 94.62 328172600 12.25892 
#> 2007-01-16 95.68 97.25 95.45 97.10 311019100 12.58023 
#> 2007-01-17 97.56 97.60 94.82 94.95 411565000 12.30168 
#> 2007-01-18 92.10 92.11 89.05 89.07 591151400 11.53987 
#> 2007-01-19 88.63 89.65 88.12 88.50 341118400 11.46602 
#> 2007-01-22 89.14 89.16 85.65 86.79 363506500 11.24447 
#> 2007-01-23 85.73 87.51 85.51 85.70 301856100 11.10325

來源

2017-03-04 21:58:01

轉換data.frame到XTS order.by需要一個適當的基於時間的對象

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