错误fread {data.table}因为它没有正确读取NAs /我想要它 [英] Error in fread{data.table} becasue its not reading NAs correctly/as I want it to
本文介绍了错误fread {data.table}因为它没有正确读取NAs /我想要它的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
这可能是一个初学者的问题，并有一个相当简单的修复，但我一直在它一段时间，似乎无法确定。我有高频数据，有大约500,000行和62列。我想使用fread（）使阅读更有效率，但问题是不是所有的行都是相同的长度。
这是我使用read.csv读取时的输出：
> df < - read.csv（file =AUROPHARMA15OCTFUT_20150916_ob.csv，header = FALSE，sep =，col.names = c（DateTime，Seq，BP1，BQ1，BO1 AP1，AQ1，AO1，BP2，BQ2，BO2，AP2，AQ2，AO2，BP3，BQ3，BO3 A5，B5，BO5，AP5，B5，B5，B5，A5，AQ3，AO3，BP4，BQ4，BO4，AP4 AQ5，AO5，BP6，BQ6，BO6，AP6，AQ6，AO6，BP7，BQ7，BO7，AP7，AQ7 A9，B9，B9，B9，A8，A8，A8， AO9，BP10，BQ10，BO10，AP10，AQ10，AO10），colClasses = c（NA，rep（integer，31） 30）））
>日期时间Seq BP1 BQ1 BO1 AP1 AQ1 AO1 BP2 BQ2 BO2 AP2 AQ2 AO2 BP3 BQ3 BO3 AP3 AQ3 AO3 BP4 BQ4 BO4 AP4 AQ4 AO4 BP5 BQ5 BO5 AP5 AQ5 AO5
1 1.442375e + 18 9905 70730 1 1 72830 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
2 1.442375e + 18 9940 70735 1 1 72830 1 1 70730 1 1 0 0 0 70285 1 1 0 0 0 70185 1 1 0 0 0 0 0 0 0 0 0
3 1.442375e + 18 10427 70905 1 1 72830 1 1 70735 3 1 0 0 0 70730 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
4 1.442375e + 18 10452 70910 1 1 72830 1 1 70905 1 1 0 0 0 70735 2 1 0 0 0 70730 1 1 0 0 0 0 0 0 0 0 0
5 1.442375e + 18 31223 70905 1 1 71805 1 1 70900 1 1 71810 1 1 70730 1 1 71815 1 1 70230 1 1 71925 3 1 70220 1 1 72075 4 1
6 1.442375e + 18 68871 70910 1 1 71405 1 1 70905 2 1 71560 4 1 70900 1 1 71625 1 1 70795 1 1 71790 2 1 70730 1 1 71800 1 1
7 1.442375e + 18 69041 70905 2 1 71405 1 1 70900 1 1 71560 4 1 70795 1 1 71625 1 1 70730 1 1 71790 2 1 70220 1 1 71800 1 1
8 1.442375e + 18 70214 70910 1 1 71405 1 1 70905 2 1 71560 4 1 70900 1 1 71625 1 1 70795 1 1 71715 2 1 70730 1 1 71790 2 1
9 1.442375e + 18 73954 70915 1 1 71405 1 1 70910 1 1 71560 4 1 70905 1 1 71625 1 1 70900 1 1 71715 2 1 70795 1 1 71800 1 1
10 1.442375e + 18 82309 71000 1 1 71405 1 1 70915 1 1 71560 5 1 70905 1 1 71625 1 1 70785 1 1 71715 2 1 70730 1 1 71780 2 1
11 1.442375e + 18 208143 71005 1 1 71500 1 1 71000 2 1 71700 4 1 70905 1 1 71705 4 1 70795 1 1 71800 1 1 70730 1 1 71840 2 1
12 1.442375e + 18 208162 71010 1 1 71500 1 1 71005 1 1 71700 4 1 71000 2 1 71705 4 1 70905 1 1 71800 1 1 70795 1 1 71840 2 1
13 1.442375e + 18 208216 71015 1 1 71500 1 1 71010 1 1 71700 4 1 71000 2 1 71705 4 1 70905 1 1 71800 1 1 70795 1 1 71840 2 1
14 1.442375e + 18 220697 71000 1 1 71500 1 1 70905 1 1 71610 4 1 70795 1 1 71705 4 1 70760 2 1 71800 1 1 70730 1 1 71840 2 1
15 1.442375e + 18 221546 71005 1 1 71500 1 1 71000 2 1 71610 4 1 70905 1 1 71705 4 1 70795 1 1 71800 1 1 70760 2 1 71840 2 1
16 1.442375e + 18 242717 71000 1 1 71435 1 1 70905 1 1 71510 6 1 70785 1 1 71675 3 1 70735 2 1 71740 2 1 70730 1 1 71790 3 1
17 1.442375e + 18 258996 71020 4 1 71435 1 1 71000 1 1 71510 6 1 70905 1 1 71570 4 1 70785 1 1 71740 2 1 70735 2 1 71790 3 1
18 1.442375e + 18 410566 71025 1 1 71495 5 1 71020 4 1 71500 1 1 71000 1 1 71600 2 1 70905 1 1 71750 2 1 70840 1 1 71800 1 1
19 1.442375e + 18 436429 71020 4 1 71495 4 1 71000 1 1 71500 1 1 70905 1 1 71655 4 1 70800 2 1 71790 2 1 70750 1 1 71800 1 1
20 1.442375e + 18 539903 71025 1 1 71435 2 1 71020 4 1 71475 2 1 71000 1 1 71500 1 1 70905 1 1 71600 4 1 70900 1 1 71625 3 1
21 1.442375e + 18 572089 71100 1 1 71435 2 1 71025 1 1 71475 2 1 71020 4 1 71500 1 1 71000 1 1 71600 4 1 70905 1 1 71635 2 1
22 1.442375e + 18 588512 71105 1 1 71480 1 1 71100 1 1 71500 1 1 71025 1 1 71590 2 1 71020 4 1 71630 2 1 71000 1 1 71640 3 1
23 1.442375e + 18 588658 71110 1 1 71500 1 1 71105 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71640 3 1 71000 1 1 71700 4 1
24 1.442375e + 18 642054 71115 1 1 71500 1 1 71110 3 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71755 4 1 71000 1 1 71800 1 1
25 1.442375e + 18 645889 71120 1 1 71500 1 1 71115 1 1 71590 2 1 71110 2 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
26 1.442375e + 18 645894 71125 1 1 71500 1 1 71120 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
27 1.442375e + 18 645897 71130 1 1 71500 1 1 71125 1 1 71590 2 1 71120 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
28 1.442375e + 18 645903 71135 1 1 71500 1 1 71130 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
29 1.442375e + 18 645911 71140 1 1 71500 1 1 71135 1 1 71590 2 1 71130 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
30 1.442375e + 18 645914 71145 1 1 71500 1 1 71140 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
31 1.442375e + 18 645917 71150 1 1 71500 1 1 71145 1 1 71590 2 1 71140 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
32 1.442375e + 18 645925 71155 1 1 71500 1 1 71150 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
33 1.442375e + 18 645928 71160 1 1 71500 1 1 71155 1 1 71590 2 1 71150 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
34 1.442375e + 18 645938 71165 1 1 71500 1 1 71160 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
35 1.442375e + 18 645966 71170 1 1 71500 1 1 71165 1 1 71590 2 1 71160 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
36 1.442375e + 18 646010 71175 1 1 71500 1 1 71170 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
37 1.442375e + 18 646028 71180 1 1 71500 1 1 71175 1 1 71590 2 1 71170 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
38 1.442375e + 18 646064 71185 1 1 71500 1 1 71180 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
39 1.442375e + 18 646077 71190 1 1 71500 1 1 71185 1 1 71590 2 1 71180 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
40 1.442375e + 18 646107 71195 1 1 71500 1 1 71190 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
41 1.442375e + 18 646132 71200 1 1 71500 1 1 71195 1 1 71590 2 1 71190 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1
42 1.442375e + 18 649141 71205 1 1 71500 1 1 71200 3 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71755 4 1 71000 1 1 71800 1 1
43 1.442375e + 18 649160 71210 1 1 71500 1 1 71205 1 1 71590 2 1 71200 2 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1
44 1.442375e + 18 659724 71100 1 1 71500 1 1 71020 4 1 71590 2 1 71000 1 1 71630 2 1 70980 2 1 71800 1 1 70940 1 1 71820 2 1
45 1.442375e + 18 659737 71105 1 1 71500 1 1 71100 1 1 71590 2 1 71020 4 1 71630 2 1 71000 1 1 71800 1 1 70980 2 1 71820 2 1
46 1.442375e + 18 659778 71110 1 1 71500 1 1 71105 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
47 1.442375e + 18 659796 71115 1 1 71500 1 1 71110 1 1 71590 2 1 71105 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
48 1.442375e + 18 659814 71120 1 1 71500 1 1 71115 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
49 1.442375e + 18 659832 71125 1 1 71500 1 1 71120 1 1 71590 2 1 71115 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
50 1.442375e + 18 659855 71130 1 1 71500 1 1 71125 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
51 1.442375e + 18 659868 71135 1 1 71500 1 1 71130 1 1 71590 2 1 71125 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
52 1.442375e + 18 659882 71140 1 1 71500 1 1 71135 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
53 1.442375e + 18 659910 71145 1 1 71500 1 1 71140 1 1 71590 2 1 71135 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
54 1.442375e + 18 659938 71150 1 1 71500 1 1 71145 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
55 1.442375e + 18 659956 71155 1 1 71500 1 1 71150 1 1 71590 2 1 71145 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
56 1.442375e + 18 659967 71160 1 1 71500 1 1 71155 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
57 1.442375e + 18 659978 71165 1 1 71500 1 1 71160 1 1 71590 2 1 71155 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
58 1.442375e + 18 660009 71170 1 1 71500 1 1 71165 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
59 1.442375e + 18 660017 71175 1 1 71500 1 1 71170 1 1 71590 2 1 71165 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
60 1.442375e + 18 660036 71180 1 1 71500 1 1 71175 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
61 1.442375e + 18 660059 71185 1 1 71500 1 1 71180 1 1 71590 2 1 71175 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
62 1.442375e + 18 660075 71190 1 1 71500 1 1 71185 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
63 1.442375e + 18 660096 71195 1 1 71500 1 1 71190 1 1 71590 2 1 71185 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
64 1.442375e + 18 660119 71200 1 1 71500 1 1 71195 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
65 1.442375e + 18 660130 71205 1 1 71500 1 1 71200 1 1 71590 2 1 71195 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
66 1.442375e + 18 660174 71210 1 1 71500 1 1 71205 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1
67 1.442375e + 18 660204 71215 1 1 71500 1 1 71210 1 1 71590 2 1 71205 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1
68 1.442375e +18 676325 71220 1 1 71500 1 1 71215 3 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71000 3 1 71825 2 1
69 1.442375e + 18 679352 71215 3 1 71500 1 1 71100 1 1 71660 2 1 71020 4 1 71700 2 1 71000 3 1 71800 1 1 70985 1 1 71825 2 1
70 1.442375e + 18 679855 71225 1 1 71500 1 1 71215 2 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71000 3 1 71825 2 1
71 1.442375e + 18 685588 71230 1 1 71500 1 1 71225 1 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1
72 1.442375e + 18 685600 71235 1 1 71500 1 1 71230 1 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1
73 1.442375e + 18 685609 71230 1 1 71500 1 1 71100 1 1 71660 2 1 71020 4 1 71700 2 1 71015 2 1 71800 1 1 70985 1 1 71835 2 1
74 1.442375e + 18 685611 71240 1 1 71500 1 1 71100 1 1 71660 2 1 71020 4 1 71700 2 1 71015 2 1 71800 1 1 70985 1 1 71835 2 1
75 1.442375e + 18 685635 71245 1 1 71500 1 1 71240 1 1 71660 2 1 71230 1 1 71700 2 1 71100 1 1 71800 1 1 71020 4 1 71835 2 1
76 1.442375e + 18 690309 71500 1 1 NA NA NA NA NA不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用不适用。 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1 70985 1 1 72000 1 1
78 1.442375e + 18 690344 71250 1 1 71660 2 1 71245 1 1 71700 2 1 71100 1 1 71800 1 1 71020 4 1 71835 2 1 71015 2 1 72000 1 1
79 1.442375e + 18 691085 71255 1 1 71655 1 1 71250 3 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1
正如你可以看到，行76是一个交易行，只有5列数据。 read.csv正确处理缺失的值，并为它们插入NAs，这是我想要fread做的，如果可能的话。
但是当我运行fread，我得到了什么：
> fdf <-fread（input =AUROPHARMA15OCTFUT_20150916_ob.csv，sep =，header = FALSE，na.strings =，data.table = FALSE）pre>
fread中出错（输入=AUROPHARMA15OCTFUT_20150916_ob.csv ，sep =，：
当读取数据时，期望的sep（''）而新行或EOF结束第76行的字段5：1442375160144000000 690309 71500 1 1
即使我指定了colClasses：
> fdf< ; - fread（input =AUROPHARMA15OCTFUT_20150916_ob.csv，sep =，header = FALSE，na.strings =，data.table = FALSE，colClasses = c（NA，rep（integer，31） （NULL，30）））
fread中出错（输入=AUROPHARMA15OCTFUT_20150916_ob.csv，sep =，：
预计sep（''），但新行或EOF结束字段5读取数据时的第76行：1442375160144000000 690309 71500 1 1
我必须更改我的na.strings参数？如果是这样，应该是什么？或者有其他方法我应该解决这个问题吗？
任何帮助，建议或替代品将不胜感激。谢谢您的帮助。
如果需要更多信息，请与我们联系。
na.strings = c（，\\\
）解决方案/ code>在你的fread（），但它不会工作在data.table版本1.9.6。这是一个
已知问题：
https://github.com/Rdatatable/data.table/issues/810
这似乎在data.table版本1.9.7中是固定的（在CRAN中不可用）。从github更新你的data.table版本并运行代码与上面的参数更改。
感谢drat仓库更新data.table到devel版本现在更容易， 安装wiki 了解详情。
This might be a beginners question and have quite a simple fix but I've been at it for a while and cant seem to figure it out. I have highfrequency data that has about 500,000 rows and 62 columns. I want to use fread() to make the reading more efficient but the problem is that not all rows are of the same length. Theres quote data and theres trade data, the trade lines have only 5 columns.
Here is my output when I read using read.csv:
> df<- read.csv(file = "AUROPHARMA15OCTFUT_20150916_ob.csv",header = FALSE,sep = "", col.names = c("DateTime","Seq","BP1","BQ1","BO1","AP1","AQ1","AO1","BP2","BQ2","BO2","AP2","AQ2","AO2","BP3","BQ3","BO3","AP3","AQ3","AO3","BP4","BQ4","BO4","AP4","AQ4","AO4","BP5","BQ5","BO5","AP5","AQ5","AO5","BP6","BQ6","BO6","AP6","AQ6","AO6","BP7","BQ7","BO7","AP7","AQ7","AO7","BP8","BQ8","BO8","AP8","AQ8","AO8","BP9","BQ9","BO9","AP9","AQ9","AO9","BP10","BQ10","BO10","AP10","AQ10","AO10"), colClasses = c(NA, rep("integer",31), rep("NULL", 30))) > head(df,100) DateTime Seq BP1 BQ1 BO1 AP1 AQ1 AO1 BP2 BQ2 BO2 AP2 AQ2 AO2 BP3 BQ3 BO3 AP3 AQ3 AO3 BP4 BQ4 BO4 AP4 AQ4 AO4 BP5 BQ5 BO5 AP5 AQ5 AO5 1 1.442375e+18 9905 70730 1 1 72830 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1.442375e+18 9940 70735 1 1 72830 1 1 70730 1 1 0 0 0 70285 1 1 0 0 0 70185 1 1 0 0 0 0 0 0 0 0 0 3 1.442375e+18 10427 70905 1 1 72830 1 1 70735 3 1 0 0 0 70730 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1.442375e+18 10452 70910 1 1 72830 1 1 70905 1 1 0 0 0 70735 2 1 0 0 0 70730 1 1 0 0 0 0 0 0 0 0 0 5 1.442375e+18 31223 70905 1 1 71805 1 1 70900 1 1 71810 1 1 70730 1 1 71815 1 1 70230 1 1 71925 3 1 70220 1 1 72075 4 1 6 1.442375e+18 68871 70910 1 1 71405 1 1 70905 2 1 71560 4 1 70900 1 1 71625 1 1 70795 1 1 71790 2 1 70730 1 1 71800 1 1 7 1.442375e+18 69041 70905 2 1 71405 1 1 70900 1 1 71560 4 1 70795 1 1 71625 1 1 70730 1 1 71790 2 1 70220 1 1 71800 1 1 8 1.442375e+18 70214 70910 1 1 71405 1 1 70905 2 1 71560 4 1 70900 1 1 71625 1 1 70795 1 1 71715 2 1 70730 1 1 71790 2 1 9 1.442375e+18 73954 70915 1 1 71405 1 1 70910 1 1 71560 4 1 70905 1 1 71625 1 1 70900 1 1 71715 2 1 70795 1 1 71800 1 1 10 1.442375e+18 82309 71000 1 1 71405 1 1 70915 1 1 71560 5 1 70905 1 1 71625 1 1 70785 1 1 71715 2 1 70730 1 1 71780 2 1 11 1.442375e+18 208143 71005 1 1 71500 1 1 71000 2 1 71700 4 1 70905 1 1 71705 4 1 70795 1 1 71800 1 1 70730 1 1 71840 2 1 12 1.442375e+18 208162 71010 1 1 71500 1 1 71005 1 1 71700 4 1 71000 2 1 71705 4 1 70905 1 1 71800 1 1 70795 1 1 71840 2 1 13 1.442375e+18 208216 71015 1 1 71500 1 1 71010 1 1 71700 4 1 71000 2 1 71705 4 1 70905 1 1 71800 1 1 70795 1 1 71840 2 1 14 1.442375e+18 220697 71000 1 1 71500 1 1 70905 1 1 71610 4 1 70795 1 1 71705 4 1 70760 2 1 71800 1 1 70730 1 1 71840 2 1 15 1.442375e+18 221546 71005 1 1 71500 1 1 71000 2 1 71610 4 1 70905 1 1 71705 4 1 70795 1 1 71800 1 1 70760 2 1 71840 2 1 16 1.442375e+18 242717 71000 1 1 71435 1 1 70905 1 1 71510 6 1 70785 1 1 71675 3 1 70735 2 1 71740 2 1 70730 1 1 71790 3 1 17 1.442375e+18 258996 71020 4 1 71435 1 1 71000 1 1 71510 6 1 70905 1 1 71570 4 1 70785 1 1 71740 2 1 70735 2 1 71790 3 1 18 1.442375e+18 410566 71025 1 1 71495 5 1 71020 4 1 71500 1 1 71000 1 1 71600 2 1 70905 1 1 71750 2 1 70840 1 1 71800 1 1 19 1.442375e+18 436429 71020 4 1 71495 4 1 71000 1 1 71500 1 1 70905 1 1 71655 4 1 70800 2 1 71790 2 1 70750 1 1 71800 1 1 20 1.442375e+18 539903 71025 1 1 71435 2 1 71020 4 1 71475 2 1 71000 1 1 71500 1 1 70905 1 1 71600 4 1 70900 1 1 71625 3 1 21 1.442375e+18 572089 71100 1 1 71435 2 1 71025 1 1 71475 2 1 71020 4 1 71500 1 1 71000 1 1 71600 4 1 70905 1 1 71635 2 1 22 1.442375e+18 588512 71105 1 1 71480 1 1 71100 1 1 71500 1 1 71025 1 1 71590 2 1 71020 4 1 71630 2 1 71000 1 1 71640 3 1 23 1.442375e+18 588658 71110 1 1 71500 1 1 71105 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71640 3 1 71000 1 1 71700 4 1 24 1.442375e+18 642054 71115 1 1 71500 1 1 71110 3 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71755 4 1 71000 1 1 71800 1 1 25 1.442375e+18 645889 71120 1 1 71500 1 1 71115 1 1 71590 2 1 71110 2 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 26 1.442375e+18 645894 71125 1 1 71500 1 1 71120 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 27 1.442375e+18 645897 71130 1 1 71500 1 1 71125 1 1 71590 2 1 71120 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 28 1.442375e+18 645903 71135 1 1 71500 1 1 71130 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 29 1.442375e+18 645911 71140 1 1 71500 1 1 71135 1 1 71590 2 1 71130 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 30 1.442375e+18 645914 71145 1 1 71500 1 1 71140 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 31 1.442375e+18 645917 71150 1 1 71500 1 1 71145 1 1 71590 2 1 71140 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 32 1.442375e+18 645925 71155 1 1 71500 1 1 71150 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 33 1.442375e+18 645928 71160 1 1 71500 1 1 71155 1 1 71590 2 1 71150 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 34 1.442375e+18 645938 71165 1 1 71500 1 1 71160 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 35 1.442375e+18 645966 71170 1 1 71500 1 1 71165 1 1 71590 2 1 71160 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 36 1.442375e+18 646010 71175 1 1 71500 1 1 71170 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 37 1.442375e+18 646028 71180 1 1 71500 1 1 71175 1 1 71590 2 1 71170 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 38 1.442375e+18 646064 71185 1 1 71500 1 1 71180 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 39 1.442375e+18 646077 71190 1 1 71500 1 1 71185 1 1 71590 2 1 71180 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 40 1.442375e+18 646107 71195 1 1 71500 1 1 71190 2 1 71590 2 1 71110 1 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 41 1.442375e+18 646132 71200 1 1 71500 1 1 71195 1 1 71590 2 1 71190 1 1 71630 2 1 71110 1 1 71755 4 1 71100 1 1 71800 1 1 42 1.442375e+18 649141 71205 1 1 71500 1 1 71200 3 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71755 4 1 71000 1 1 71800 1 1 43 1.442375e+18 649160 71210 1 1 71500 1 1 71205 1 1 71590 2 1 71200 2 1 71630 2 1 71100 1 1 71755 4 1 71020 4 1 71800 1 1 44 1.442375e+18 659724 71100 1 1 71500 1 1 71020 4 1 71590 2 1 71000 1 1 71630 2 1 70980 2 1 71800 1 1 70940 1 1 71820 2 1 45 1.442375e+18 659737 71105 1 1 71500 1 1 71100 1 1 71590 2 1 71020 4 1 71630 2 1 71000 1 1 71800 1 1 70980 2 1 71820 2 1 46 1.442375e+18 659778 71110 1 1 71500 1 1 71105 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 47 1.442375e+18 659796 71115 1 1 71500 1 1 71110 1 1 71590 2 1 71105 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 48 1.442375e+18 659814 71120 1 1 71500 1 1 71115 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 49 1.442375e+18 659832 71125 1 1 71500 1 1 71120 1 1 71590 2 1 71115 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 50 1.442375e+18 659855 71130 1 1 71500 1 1 71125 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 51 1.442375e+18 659868 71135 1 1 71500 1 1 71130 1 1 71590 2 1 71125 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 52 1.442375e+18 659882 71140 1 1 71500 1 1 71135 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 53 1.442375e+18 659910 71145 1 1 71500 1 1 71140 1 1 71590 2 1 71135 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 54 1.442375e+18 659938 71150 1 1 71500 1 1 71145 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 55 1.442375e+18 659956 71155 1 1 71500 1 1 71150 1 1 71590 2 1 71145 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 56 1.442375e+18 659967 71160 1 1 71500 1 1 71155 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 57 1.442375e+18 659978 71165 1 1 71500 1 1 71160 1 1 71590 2 1 71155 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 58 1.442375e+18 660009 71170 1 1 71500 1 1 71165 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 59 1.442375e+18 660017 71175 1 1 71500 1 1 71170 1 1 71590 2 1 71165 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 60 1.442375e+18 660036 71180 1 1 71500 1 1 71175 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 61 1.442375e+18 660059 71185 1 1 71500 1 1 71180 1 1 71590 2 1 71175 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 62 1.442375e+18 660075 71190 1 1 71500 1 1 71185 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 63 1.442375e+18 660096 71195 1 1 71500 1 1 71190 1 1 71590 2 1 71185 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 64 1.442375e+18 660119 71200 1 1 71500 1 1 71195 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 65 1.442375e+18 660130 71205 1 1 71500 1 1 71200 1 1 71590 2 1 71195 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 66 1.442375e+18 660174 71210 1 1 71500 1 1 71205 2 1 71590 2 1 71100 1 1 71630 2 1 71020 4 1 71800 1 1 71000 1 1 71820 2 1 67 1.442375e+18 660204 71215 1 1 71500 1 1 71210 1 1 71590 2 1 71205 1 1 71630 2 1 71100 1 1 71800 1 1 71020 4 1 71820 2 1 68 1.442375e+18 676325 71220 1 1 71500 1 1 71215 3 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71000 3 1 71825 2 1 69 1.442375e+18 679352 71215 3 1 71500 1 1 71100 1 1 71660 2 1 71020 4 1 71700 2 1 71000 3 1 71800 1 1 70985 1 1 71825 2 1 70 1.442375e+18 679855 71225 1 1 71500 1 1 71215 2 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71000 3 1 71825 2 1 71 1.442375e+18 685588 71230 1 1 71500 1 1 71225 1 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1 72 1.442375e+18 685600 71235 1 1 71500 1 1 71230 1 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1 73 1.442375e+18 685609 71230 1 1 71500 1 1 71100 1 1 71660 2 1 71020 4 1 71700 2 1 71015 2 1 71800 1 1 70985 1 1 71835 2 1 74 1.442375e+18 685611 71240 1 1 71500 1 1 71100 1 1 71660 2 1 71020 4 1 71700 2 1 71015 2 1 71800 1 1 70985 1 1 71835 2 1 75 1.442375e+18 685635 71245 1 1 71500 1 1 71240 1 1 71660 2 1 71230 1 1 71700 2 1 71100 1 1 71800 1 1 71020 4 1 71835 2 1 76 1.442375e+18 690309 71500 1 1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 77 1.442375e+18 690309 71245 1 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1 70985 1 1 72000 1 1 78 1.442375e+18 690344 71250 1 1 71660 2 1 71245 1 1 71700 2 1 71100 1 1 71800 1 1 71020 4 1 71835 2 1 71015 2 1 72000 1 1 79 1.442375e+18 691085 71255 1 1 71655 1 1 71250 3 1 71660 2 1 71100 1 1 71700 2 1 71020 4 1 71800 1 1 71015 2 1 71835 2 1As you can see row 76 is a trade line and has data only in 5 columns. read.csv handles the missing values correctly and inserts NAs for them, this is what I want fread to do if it is possible.
But when I run fread, this is what I get:
> fdf<- fread(input = "AUROPHARMA15OCTFUT_20150916_ob.csv", sep = " ", header = FALSE, na.strings = " ", data.table = FALSE) Error in fread(input = "AUROPHARMA15OCTFUT_20150916_ob.csv", sep = " ", : Expected sep (' ') but new line or EOF ends field 5 on line 76 when reading data: 1442375160144000000 690309 71500 1 1Even when I specify the colClasses:
> fdf<- fread(input = "AUROPHARMA15OCTFUT_20150916_ob.csv", sep = " ", header = FALSE, na.strings = "", data.table = FALSE, colClasses = c(NA, rep("integer",31), rep("NULL", 30))) Error in fread(input = "AUROPHARMA15OCTFUT_20150916_ob.csv", sep = " ", : Expected sep (' ') but new line or EOF ends field 5 on line 76 when reading data: 1442375160144000000 690309 71500 1 1Do I have to change my na.strings argument? If so, what should it be? Or is there some other way I should be tackling this issue? Any help, suggestions or alternatives will be appreciated. Thanks for the help.
Let me know if any more info is needed.
解决方案you can use
na.strings = c(" ","\n")in your fread(), but it won't work in data.table version 1.9.6 . It is a known issue:This appears to be fixed in data.table version 1.9.7 (not available in CRAN though). Update your data.table version from github and run the code with the above parameter changes.
Thanks to drat repositories updating data.table to devel version is now much easier, see Installation wiki for details.
这篇关于错误fread {data.table}因为它没有正确读取NAs /我想要它的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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