在R中使用'na.strings'和'fClass'参数读取数据时错误的列模式

Question

Windows 8.1,R版本3.1.1(2014-07-10),系统x86_64,mingw32

我有一个包含大量观察的文件(这里).这是文件中的一些字符串

Date;Time;Global_active_power;Global_reactive_power;Voltage;Global_intensity;Sub_metering_1;Sub_metering_2;Sub_metering_3
16/12/2006;17:24:00;4.216;0.418;234.840;18.400;0.000;1.000;17.000
16/12/2006;17:25:00;5.360;0.436;233.630;23.000;0.000;1.000;16.000
28/4/2007;00:20:00;0.492;0.208;236.240;2.200;0.000;0.000;0.000
28/4/2007;00:21:00;?;?;?;?;?;?;
21/12/2006;11:25:00;0.246;0.000;241.740;1.000;0.000;0.000;0.000
21/12/2006;11:26:00;0.246;0.000;241.830;1.000;0.000;0.000;0.000

NA值用"？"表示.我正在尝试阅读该文件

epcData <- fread(dataFile,
                 sep = ";",
                 header = TRUE,
                 na.strings = "?",
                 colClasses = c("character", "character", rep("numeric", 7)),
                 stringsAsFactors = FALSE)

我有警告像:

Bumped column 3 to type character on data row 10, field contains '?'. Coercing previously read values in this column from integer or numeric back to character which may not be lossless; e.g., if '00' and '000' occurred before they will now be just '0', and there may be inconsistencies with treatment of ',,' and ',NA,' too (if they occurred in this column before the bump). If this matters please rerun and set 'colClasses' to 'character' for this column. Please note that column type detection uses the first 5 rows, the middle 5 rows and the last 5 rows, so hopefully this message should be very rare. If reporting to datatable-help, please rerun and include the output from verbose=TRUE.

第10行是

   28/4/2007;00:21:00;?;?;?;?;?;?;

epcData [10]

版画

         Date     Time Global_active_power Global_reactive_power Voltage
1: 28/4/2076 00:21:00                  NA                    NA      NA
   Global_intensity Sub_metering_1 Sub_metering_2 Sub_metering_3
1:               NA             NA             NA             NA

但是所有列的模式都是"字符",即使对于列3:9(但是colClasses = c("character","character",rep("numeric",7))).

出了什么问题？

Answer 1

截至今天，该data.table软件包的版本为 1.12.2。这不再是问题，上述 csv 数据的导入工作完美，所有问号都替换为NAs