csv中的双引号元素不能用pandas读取

I have an input file where every value is stored as a string. It is inside a csv file with each entry inside double quotes.

我有一个输入文件，其中每个值都存储为一个字符串。它位于一个csv文件中，每个条目都在双引号内。

Example file:

示例文件：

"column1","column2", "column3", "column4", "column5", "column6"
"AM", "07", "1", "SD", "SD", "CR"
"AM", "08", "1,2,3", "PR,SD,SD", "PR,SD,SD", "PR,SD,SD"
"AM", "01", "2", "SD", "SD", "SD"

There are only six columns. What options do I need to enter to pandas read_csv to read this correctly?

只有六列。我需要输入哪些选项来pandas read_csv才能正确读取？

I currently am trying:

我目前正在尝试：

import pandas as pd
df = pd.read_csv(file, quotechar='"')

but this gives me the error message: CParserError: Error tokenizing data. C error: Expected 6 fields in line 3, saw 14

但这给了我错误消息：CParserError：错误标记数据。 C错误：第3行预计6个字段，见14

Which obviously means that it is ignoring the '"' and parsing every comma as a field. However, for line 3, columns 3 through 6 should be strings with commas in them. ("1,2,3", "PR,SD,SD", "PR,SD,SD", "PR,SD,SD")

这显然意味着它忽略了'''并将每个逗号解析为一个字段。但是，对于第3行，第3列到第6列应该是带逗号的字符串。（“1,2,3”，“PR，SD ，SD“，”PR，SD，SD“，”PR，SD，SD“）

How do I get pandas.read_csv to parse this correctly?

如何让pandas.read_csv正确解析？

Thanks.

谢谢。

1 个解决方案

#1

This will work. It falls back to the python parser (as you have non-regular separators, e.g. they are comma and sometimes space). If you only have commas it would use the c-parser and be much faster.

这会奏效。它回退到python解析器（因为你有非常规的分隔符，例如它们是逗号，有时是空格）。如果你只有逗号，它将使用c-parser并且速度更快。

In [1]: import csv

In [2]: !cat test.csv
"column1","column2", "column3", "column4", "column5", "column6"
"AM", "07", "1", "SD", "SD", "CR"
"AM", "08", "1,2,3", "PR,SD,SD", "PR,SD,SD", "PR,SD,SD"
"AM", "01", "2", "SD", "SD", "SD"

In [3]: pd.read_csv('test.csv',sep=',\s+',quoting=csv.QUOTE_ALL)
pandas/io/parsers.py:637: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators; you can avoid this warning by specifying engine='python'.
  ParserWarning)
Out[3]: 
     "column1","column2" "column3"   "column4"   "column5"   "column6"
"AM"                "07"       "1"        "SD"        "SD"        "CR"
"AM"                "08"   "1,2,3"  "PR,SD,SD"  "PR,SD,SD"  "PR,SD,SD"
"AM"                "01"       "2"        "SD"        "SD"        "SD"