在传递给熊猫之前检查编码。它会让你慢下来，但是……

with open(path, 'r') as f:
    encoding = f.encoding 

df = pd.read_csv(path,sep=sep, encoding=encoding)

在python 3.7中

最简单的解决方案:

import pandas as pd
df = pd.read_csv('file_name.csv', engine='python')

替代解决方案:

崇高的文本:

在Sublime文本编辑器或VS Code中打开csv文件。 以utf-8格式保存。 在sublime中，单击File -> Save with encoding -> UTF-8

VS代码:

在VSCode的底部栏中，您将看到标签UTF-8。点击它。弹出窗口会打开。单击“保存编码”。现在可以为该文件选择新的编码。

然后，您可以像往常一样读取您的文件:

import pandas as pd
data = pd.read_csv('file_name.csv', encoding='utf-8')

其他不同的编码类型有:

encoding = "cp1252"
encoding = "ISO-8859-1"

Read_csv接受一个编码选项来处理不同格式的文件。我主要使用read_csv('file'， encoding = "ISO-8859-1")，或者encoding = "utf-8"用于读取，通常utf-8用于to_csv。

你也可以使用一些别名选项，如'latin'或'cp1252' (Windows)，而不是'ISO-8859-1'(参见python文档，也可以了解您可能遇到的许多其他编码)。

参见相关熊猫文件， 关于csv文件的python文档示例，以及大量关于SO的相关问题。一个很好的背景资源是每个开发人员都应该知道unicode和字符集。

要检测编码(假设文件包含非ascii字符)，可以使用enca(参见手册页)或file -i (linux)或file -i (osx)(参见手册页)。

Pandas允许指定编码，但不允许忽略错误，不允许自动替换违规字节。因此，没有一种适合所有情况的方法，而是根据实际用例使用不同的方法。

You know the encoding, and there is no encoding error in the file. Great: you have just to specify the encoding: file_encoding = 'cp1252' # set file_encoding to the file encoding (utf8, latin1, etc.) pd.read_csv(input_file_and_path, ..., encoding=file_encoding) You do not want to be bothered with encoding questions, and only want that damn file to load, no matter if some text fields contain garbage. Ok, you only have to use Latin1 encoding because it accept any possible byte as input (and convert it to the unicode character of same code): pd.read_csv(input_file_and_path, ..., encoding='latin1') You know that most of the file is written with a specific encoding, but it also contains encoding errors. A real world example is an UTF8 file that has been edited with a non utf8 editor and which contains some lines with a different encoding. Pandas has no provision for a special error processing, but Python open function has (assuming Python3), and read_csv accepts a file like object. Typical errors parameter to use here are 'ignore' which just suppresses the offending bytes or (IMHO better) 'backslashreplace' which replaces the offending bytes by their Python’s backslashed escape sequence: file_encoding = 'utf8' # set file_encoding to the file encoding (utf8, latin1, etc.) input_fd = open(input_file_and_path, encoding=file_encoding, errors = 'backslashreplace') pd.read_csv(input_fd, ...)

这个答案似乎是CSV编码问题的万能答案。如果你的头文件出现了奇怪的编码问题，就像这样:

>>> f = open(filename,"r")
>>> reader = DictReader(f)
>>> next(reader)
OrderedDict([('\ufeffid', '1'), ... ])

然后在CSV文件的开头有一个字节顺序标记(BOM)字符。这个答案解决了这个问题:

Python读取csv - BOM嵌入到第一个键

解决方案是用encoding="utf-8-sig"加载CSV:

>>> f = open(filename,"r", encoding="utf-8-sig")
>>> reader = DictReader(f)
>>> next(reader)
OrderedDict([('id', '1'), ... ])

希望这能帮助到一些人。

在我的例子中，这适用于python 2.7:

data = read_csv(filename, encoding = "ISO-8859-1", dtype={'name_of_colum': unicode}, low_memory=False) 

对于python3，只有:

data = read_csv(filename, encoding = "ISO-8859-1", low_memory=False)