在pandas中使用read_csv时忽略双引号（“）

Question

================================================== ====
Title: Whole case
Location: oyuri
From: Aki 
Date: 2018/11/30 (Friday) 11:55:29
================================================== =====
1: Aki 
2018/12/05 (Wed) 17:33:17
"
An approval notice has been sent.
-------------------------------------------------- ------------------
2: Aki
2018/12/06 (Thursday) 17:14:30
I was notified by Mr. Id, the agent of the other party.

-------------------------------------------------- ------------------
3: kano, etc.
2018/12/07 (Friday) 11:44:45
Please call rito.
-------------------------------------------------- ------------------

这是我的文本文件，我已将其转换为CSV 我面临的唯一问题是文件中有双引号（“）时（例如，在条目号1的文件中） 如何在读取CSV文件时忽略双引号？ 读取文件时使用的分隔符为\n

df = pd.read_csv(filename ,sep='\n', header=None)

Answer 1

这是：

df = pd.read_csv('sample.csv' ,sep='\n', header=None, quotechar="'")
print(df)

#output:
                                                    0
0   ==============================================...
1                                   Title: Whole case
2                                     Location: oyuri
3                                           From: Aki
4                  Date: 2018/11/30 (Friday) 11:55:29
5   ==============================================...
6                                              1: Aki
7                           2018/12/05 (Wed) 17:33:17
8                                                   "
9                   An approval notice has been sent.
10                         ...
11                                             2: Aki
12                     2018/12/06 (Thursday) 17:14:30
13  I was notified by Mr. Id, the agent of the oth...
14                         ...
15                                      3: kano, etc.
16                       2018/12/07 (Friday) 11:44:45
17                                  Please call rito.
18                         ...

Answer 2

尝试传递quoting = csv.QUOTE_NONE或（如果不起作用）玩quotechar

import csv

df = pd.read_csv(filename, sep='\n', header=None, quoting=csv.QUOTE_NONE)