您可以将boolean indexing和条件一起使用isin，Series通过~以下方式反转布尔值：
import pandas as pd
USERS = pd.DataFrame({'email':['a@g.com','b@g.com','b@g.com','c@g.com','d@g.com']})
print (USERS)
email
0 a@g.com
1 b@g.com
2 b@g.com
3 c@g.com
4 d@g.com
EXCLUDE = pd.DataFrame({'email':['a@g.com','d@g.com']})
print (EXCLUDE)
email
0 a@g.com
1 d@g.com
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 b@g.com
2 b@g.com
3 c@g.com
df = pd.merge(USERS, EXCLUDE, how='outer', indicator=True)
print (df)
email _merge
0 a@g.com both
1 b@g.com left_only
2 b@g.com left_only
3 c@g.com left_only
4 d@g.com both
print (df.loc[df._merge == 'left_only', ['email']])
email
1 b@g.com
2 b@g.com
3 c@g.com
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