pandas 如何用一个值替换多个值python
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/46920454/
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
how to replace multiple values with one value python
提问by Jiayang Zhuo
How can I replace the data 'Beer','Alcohol','Beverage','Drink'with only 'Drink'.
如何'Beer','Alcohol','Beverage','Drink'仅用'Drink'.
df.replace(['Beer','Alcohol','Beverage','Drink'],'Drink')
doesn't work
不起作用
回答by cs95
You almosthad it. You need to pass a dictionary to df.replace.
你几乎拥有它。您需要将字典传递给df.replace.
df
Col1
0 Beer
1 Alcohol
2 Beverage
3 Drink
df.replace(dict.fromkeys(['Beer','Alcohol','Beverage','Drink'], 'Drink'))
Col1
0 Drink
1 Drink
2 Drink
3 Drink
This works for exact matches and replacements. For partial matches and substring matching, use
这适用于精确匹配和替换。对于部分匹配和子串匹配，使用
df.replace(
dict.fromkeys(['Beer','Alcohol','Beverage','Drink'], 'Drink'),
regex=True
)
This is not an in-place operation so don't forget to assign the result back.
这不是就地操作，所以不要忘记将结果分配回来。
回答by MaxU
Try the following approach:
尝试以下方法：
lst = ['Beer','Alcohol','Beverage','Drink']
pat = r"\b(?:{})\b".format('|'.join(lst))
df = df.replace(pat, 'Drink', regexp=True)
回答by YOBEN_S
Looks like different from MaxU's solution :)
看起来与 MaxU 的解决方案不同:)
df.replace({'|'.join(['Beer','Alcohol','Beverage','Drink']):'Drink'},regex=True)
回答by Yashodhan Pawar
Slight change in earlier answers: Following code Replacing values of specific column/Columns
较早的答案略有变化：以下代码替换特定列/列的值
df[['Col1']] = df[['Col1']].replace(dict.fromkeys(['Beer','Alcohol','Beverage','Drink'], 'Drink'))
