r - fread() 失败，integer64 列中缺少值

Question

阅读下面的文本时，fread() 无法检测到第 8 列和第 9 列中的缺失值。这仅适用于默认选项 integer64="integer64" 。正确设置 integer64="double" 或 "character" 可检测 NA。请注意，该文件在 V8 和 V9 中具有三种可能的 NA——,,； ,,;和NA。附加 na.strings=c("NA","N/A","",""), sep="," 作为选项无效。

使用 read.csv() 的工作方式与 fread(integer="double") 相同。

要阅读的文本(也available as a file integer64_and_NA.csv):

2012,276,,0,"S1","001",1,,724135215,1590915056,
2012,276,2,8,"S1","001",1, ,,154598,0
2012,276,2,12,"S1","001",1,NA,5118863,21819477,
2012,276,2,0,"S1","011",8,3127133583,3127133583,9003982501,0

这是 fread() 的输出:

DT <- fread(input="integer64_and_NA.csv", verbose=TRUE, integer64="integer64", na.strings=c("NA","N/A",""," "), sep=",")

Input contains no \n. Taking this to be a filename to open
Detected eol as \r\n (CRLF) in that order, the Windows standard.
Looking for supplied sep ',' on line 4 (the last non blank line in the first 'autostart') ... found ok
Found 11 columns
First row with 11 fields occurs on line 1 (either column names or first row of data)
Some fields on line 1 are not type character (or are empty). Treating as a data row and using default column names.
Count of eol after first data row: 5
Subtracted 1 for last eol and any trailing empty lines, leaving 4 data rows
Type codes: 11114412221 (first 5 rows)
Type codes: 11114412221 (after applying colClasses and integer64)
Type codes: 11114412221 (after applying drop or select (if supplied)
Allocating 11 column slots (11 - 0 NULL)
   0.000s (  0%) Memory map (rerun may be quicker)
   0.000s (  0%) sep and header detection
   0.000s (  0%) Count rows (wc -l)
   0.000s (  0%) Column type detection (first, middle and last 5 rows)
   0.000s (  0%) Allocation of 4x11 result (xMB) in RAM
   0.000s (  0%) Reading data
   0.000s (  0%) Allocation for type bumps (if any), including gc time if triggered
   0.000s (  0%) Coercing data already read in type bumps (if any)
   0.000s (  0%) Changing na.strings to NA
   0.001s        Total

生成的 data.table 为:

DT
     V1  V2 V3 V4 V5  V6 V7                  V8                  V9        V10 V11
1: 2012 276 NA  0 S1 001  1 9218868437227407266           724135215 1590915056  NA
2: 2012 276  2  8 S1 001  1 9218868437227407266 9218868437227407266     154598   0
3: 2012 276  2 12 S1 001  1 9218868437227407266             5118863   21819477  NA
4: 2012 276  2  0 S1 011  8          3127133583          3127133583 9003982501   0

在不是 integer64 的列中正确检测到

NA 值。对于 V8 和 V9，fread() 标记为 integer64，而不是 NA，我们有“9218868437227407266”。 有趣的是，str() 将 V8 和 V9 的相应值返回为 NA:

str(DT)

Classes ‘data.table’ and 'data.frame':  4 obs. of  11 variables:
 $ V1 : int  2012 2012 2012 2012
 $ V2 : int  276 276 276 276
 $ V3 : int  NA 2 2 2
 $ V4 : int  0 8 12 0
 $ V5 : chr  "S1" "S1" "S1" "S1"
 $ V6 : chr  "001" "001" "001" "011"
 $ V7 : int  1 1 1 8
 $ V8 :Class 'integer64'  num [1:4] NA NA NA 1.55e-314
 $ V9 :Class 'integer64'  num [1:4] 3.58e-315 NA 2.53e-317 1.55e-314
 $ V10:Class 'integer64'  num [1:4] 7.86e-315 7.64e-319 1.08e-316 4.45e-314
 $ V11: int  NA 0 NA 0
 - attr(*, ".internal.selfref")=<externalptr> 

...但没有其他东西将它们视为NA:

is.na(DT$V8)
[1] FALSE FALSE FALSE FALSE
max(DT$V8)
integer64
[1] 9218868437227407266
> max(DT$V8, na.rm=TRUE)
integer64
[1] 9218868437227407266
> class(DT$V8)
[1] "integer64"
> typeof(DT$V8)
[1] "double"

这似乎不仅仅是打印/屏幕问题，data.table 将它们视为巨大的整数:

DT[, V12:=as.numeric(V8)]
Warning message:
In as.double.integer64(V8) :
  integer precision lost while converting to double
> DT
     V1  V2 V3 V4 V5  V6 V7                  V8                  V9        V10 V11          V12
1: 2012 276 NA  0 S1 001  1 9218868437227407266           724135215 1590915056  NA 9.218868e+18
2: 2012 276  2  8 S1 001  1 9218868437227407266 9218868437227407266     154598   0 9.218868e+18
3: 2012 276  2 12 S1 001  1 9218868437227407266             5118863   21819477  NA 9.218868e+18
4: 2012 276  2  0 S1 011  8          3127133583          3127133583 9003982501   0 3.127134e+09

我是否遗漏了有关 integer64 的内容，或者这是一个错误？如上所述，我可以使用 integer64="double" 来解决，但可能会丢失一些精度，如帮助文件中所述。但意外的行为是使用默认的 integer64...

这是在运行 Revolution R 3.0.2 的 Windows 8.1 64 位计算机以及运行 kubuntu 13.10、CRAN-R 3.0.2 的虚拟机上完成的。使用 CRAN 的最新稳定 data.table(截至 2014 年 2 月 7 日的 1.8.10)和 1.8.11(修订版 1110，2014-02-04 02:43:19，从 zip 手动安装为 r-forge)进行测试Windows 上的构建已损坏)，Linux 上只有稳定的 1.8.10。 bit64 已安装并加载到两台机器上。

> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-w64-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] bit64_0.9-3       bit_1.1-11        gdata_2.13.2      xts_0.9-7         zoo_1.7-10        nlme_3.1-113      hexbin_1.26.3     lattice_0.20-24   ggplot2_0.9.3.1  
[10] plyr_1.8          reshape2_1.2.2    data.table_1.8.11 Revobase_7.0.0    RevoMods_7.0.0    RevoScaleR_7.0.0 

loaded via a namespace (and not attached):
 [1] codetools_0.2-8    colorspace_1.2-4   dichromat_2.0-0    digest_0.6.4       foreach_1.4.1      gtable_0.1.2       gtools_3.2.1       iterators_1.0.6   
 [9] labeling_0.2       MASS_7.3-29        munsell_0.4.2      proto_0.3-10       RColorBrewer_1.0-5 reshape_0.8.4      scales_0.2.3       stringr_0.6.2     
[17] tools_3.0.2      

Answer 1

这个错误，#488 ，现已修复为 this commit在 data.table v1.9.5 的开发版本中，如果加载了 bit64，则值将正确分配(并显示)为 NA。 p>

require(data.table) # v1.9.5
require(bit64)
ans = fread("test.csv")
#      V1  V2 V3 V4 V5  V6 V7         V8         V9        V10 V11
# 1: 2012 276 NA  0 S1 001  1         NA  724135215 1590915056  NA
# 2: 2012 276  2  8 S1 001  1         NA         NA     154598   0
# 3: 2012 276  2 12 S1 001  1         NA    5118863   21819477  NA
# 4: 2012 276  2  0 S1 011  8 3127133583 3127133583 9003982501   0