pandas 删除熊猫数据框中的特殊字符
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/45871731/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Removing special characters in a pandas dataframe
提问by SKlein
I have found information on how this could be done, but nothing has worked for me. I am trying to replace the special character 'e'. I imported my data from a csv file and I used encoding='latin1' or else I kept getting errors. However, a simple DF['Column'].str.replace('e', '') will not do the trick. I also tried decoding and using the hex value for that character which was recommended on another post, but that still won't work for me. Help is very much appreciated, and I am willing to post code if necessary.
我找到了有关如何做到这一点的信息，但对我来说没有任何效果。我正在尝试替换特殊字符“e”。我从一个 csv 文件导入了我的数据，我使用了 encoding='latin1' 否则我一直收到错误。然而，一个简单的 DF['Column'].str.replace('e', '') 不会成功。我还尝试解码并使用另一篇文章中推荐的该字符的十六进制值，但这对我仍然不起作用。非常感谢帮助，如有必要，我愿意发布代码。
回答by cs95
Call str.encodefollowed by str.decode:
调用str.encode后跟str.decode：
df.YourCol.str.encode('utf-8').str.decode('ascii', 'ignore')
If you want to do this for multiple columns, you can slice and call df.applymap:
如果要对多列执行此操作，可以切片并调用df.applymap：
df[col_list].applymap(lambda x: x.encode('utf-8').decode('ascii', 'ignore'))
Remember that these operations are not in-place. So, you'll have to assign those columns back to their rightful place.
请记住，这些操作不是就地的。因此，您必须将这些列分配回其应有的位置。
