Mysql 在R中使用read.csv和read.table读取数据时出现问题

我有一个使用以下命令从mysql导出的数据

SELECT 
    id_code,info_text INTO OUTFILE '/tmp/company-desc.csv' 
    FIELDS TERMINATED BY ';' 
    OPTIONALLY ENCLOSED BY '"' 
    LINES TERMINATED BY '\n'
FROM 
    dx_company WHERE LENGTH(id_code) = 8 AND 
    id_code REGEXP '^[0-9]+$';

但是当我尝试在R中使用以下命令加载csv时

 dt.companydesc <- read.csv("company-desc.csv",sep=';',fill=T, encoding = "UTF-8",quote="\n",header=FALSE)

有些id与描述混淆。 它在阅读时基本上存在引号和\n问题。如果我想把这两个都给我，我会打乱整张桌子。 我还尝试了gsub和readLines。 任何帮助

快照：CSV文件

  "1000004";"general"
  "1000000";"licensed version, and products"
  "1000007";""
  "1000003";""
  "1000002";""
  "1000006";""
  "1000002";"automobiles; well organised"

期望输出：

   Id_code  Description
  1000004  general
  1000000  licensed version, and products
  1000007  NA
  1000003  NA
  1000002  NA
  1000006  NA
  1000002  automobiles and industry; well organised

下面是一种使用data.table:：fread的方法，它也更快：

require(data.table) # v1.9.6+
fread('  "1000004";"general"
  "1000000";"licensed version, and products"
  "1000007";""
  "1000003";""
  "1000002";""
  "1000006";""
  "1000002";"automobiles; well organised"', na.strings="", 
header=FALSE, col.names=c("Id_code", "Description"))

#    Id_code                    Description
# 1: 1000004                        general
# 2: 1000000 licensed version, and products
# 3: 1000007                             NA
# 4: 1000003                             NA
# 5: 1000002                             NA
# 6: 1000006                             NA
# 7: 1000002    automobiles; well organised

---

随预期输出一起发布一个示例。我猜您的quote参数不正确，但如果没有看到CSV文件的示例，我无法确定。quote=\n有点不可见。您对MySQL说分隔符是逗号，然后使用；当您调用read.csv时。你确定吗？抱歉，我更正了mysql语句，我实际上尝试了使用不同的分隔符。我可以使用read.csv2轻松读取快照。他们可能应该避免CSV步骤，并从R查询数据库。

   Id_code  Description
  1000004  general
  1000000  licensed version, and products
  1000007  NA
  1000003  NA
  1000002  NA
  1000006  NA
  1000002  automobiles and industry; well organised

require(data.table) # v1.9.6+
fread('  "1000004";"general"
  "1000000";"licensed version, and products"
  "1000007";""
  "1000003";""
  "1000002";""
  "1000006";""
  "1000002";"automobiles; well organised"', na.strings="", 
header=FALSE, col.names=c("Id_code", "Description"))

#    Id_code                    Description
# 1: 1000004                        general
# 2: 1000000 licensed version, and products
# 3: 1000007                             NA
# 4: 1000003                             NA
# 5: 1000002                             NA
# 6: 1000006                             NA
# 7: 1000002    automobiles; well organised