在 Pandas 中，如何从基于另一个数据帧的数据帧中删除行？
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In Pandas, how to delete rows from a Data Frame based on another Data Frame?
提问by Vini
I have 2 Data Frames, one named USERS and another named EXCLUDE. Both of them have a field named "email".
我有 2 个数据帧，一个名为 USERS，另一个名为 EXCLUDE。他们都有一个名为“电子邮件”的字段。
Basically, I want to remove every row in USERS that has an email contained in EXCLUDE.
基本上，我想删除 USERS 中包含在 EXCLUDE 中的电子邮件的每一行。
How can I do it?
我该怎么做？
回答by jezrael
You can use boolean indexingand condition with isin, inverting boolean Seriesis by ~:
您可以使用boolean indexing和条件isin，反转布尔值Series是~：
import pandas as pd
USERS = pd.DataFrame({'email':['[email protected]','[email protected]','[email protected]','[email protected]','[email protected]']})
print (USERS)
email
0 [email protected]
1 [email protected]
2 [email protected]
3 [email protected]
4 [email protected]
EXCLUDE = pd.DataFrame({'email':['[email protected]','[email protected]']})
print (EXCLUDE)
email
0 [email protected]
1 [email protected]
print (USERS.email.isin(EXCLUDE.email))
0 True
1 False
2 False
3 False
4 True
Name: email, dtype: bool
print (~USERS.email.isin(EXCLUDE.email))
0 False
1 True
2 True
3 True
4 False
Name: email, dtype: bool
print (USERS[~USERS.email.isin(EXCLUDE.email)])
email
1 [email protected]
2 [email protected]
3 [email protected]
Another solution with merge:
另一个解决方案merge：
df = pd.merge(USERS, EXCLUDE, how='outer', indicator=True)
print (df)
email _merge
0 [email protected] both
1 [email protected] left_only
2 [email protected] left_only
3 [email protected] left_only
4 [email protected] both
print (df.loc[df._merge == 'left_only', ['email']])
email
1 [email protected]
2 [email protected]
3 [email protected]
