pandas 中的转义引号read_csv [英] Escaped quotes in pandas read_csv

问题描述

使用 read_csv .
(注意:R的read.csv可以正常工作.)

I am unable to create a dataframe which has escaped quotes when using read_csv.
(Note: R's read.csv works as expected.)

import pandas as pd
pd.read_csv('data.csv')
#error!
CParserError: Error tokenizing data. C error: Expected 2 fields in line 4, saw 3

data.csv

SEARCH_TERM,ACTUAL_URL
"bra tv bord","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"
"tv på hjul","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"
"SLAGBORD, \"Bergslagen\", IKEA:s 1700-tals serie","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"

如何阅读此csv并避免出现此错误?

How can I read this csv and avoid this error?

我的猜测是，pandas使用的某些正则表达式无法处理歧义和第三行的跳动，或更具体地说:\"Bergslagen\".

推荐答案

它确实有效，但是您必须为嵌入的引号指出转义字符:

It does work, but you have to indicate the escape character for the embedded quotes:

In [1]: data = '''SEARCH_TERM,ACTUAL_URL
"bra tv bord","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"
"tv p\xc3\xa5 hjul","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"
"SLAGBORD, \\"Bergslagen\\", IKEA:s 1700-tals serie","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"'''

In [2]: df = read_csv(StringIO(data), escapechar='\\', encoding='utf-8')

In [3]: df
Out[3]: 
                                      SEARCH_TERM                                         ACTUAL_URL
0                                     bra tv bord  http://www.ikea.com/se/sv/catalog/categories/d...
1                                      tv på hjul  http://www.ikea.com/se/sv/catalog/categories/d...
2  SLAGBORD, "Bergslagen", IKEA:s 1700-tals serie  http://www.ikea.com/se/sv/catalog/categories/d...

请参阅此要点.

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