Pandas：如何使用其他 dataframe 的列值从 dataframe 返回具有相同行值的行？

Question

import pandas as pd

df1 = pd.DataFrame({'country': ['EUR.1M', 'EUR.1M', 'EUR.3M','EUR.3M','EUR.6M','EUR.6M','USD.3M', 'USD.3M', 'USD.3M', 
                        'HKD.3M','HKD.3M','HKD.3M','GBP.6M', 'GBP.6M','GBP.6M'], 
       'inst': ['base', 'base', 'depo', 'Fut', 'Fut','base', 'irs','base', 'irs','Fut', 'irs', 'irs',
                'irs','Fut', 'irs'],
       'frequency' : ['Eur35Y', 'Eur40Y', 'Eur12Y','Eur10Y','Eur20Y','Eur40Y','USDIRS23Y', 'USDswap15Y','USD20Y',
                      'HKD50Y', 'HKD20Y','HKD10Y','GBP19Y', 'GBPIRS15Y','GBP60Y']})

df2 = pd.DataFrame({'tenor': ['Eur40Y','HKD50Y']})

I have two dataframes mentioned above and I am interested in two columns from df1 ('country'and 'frequency'). However, am trying to pull values from column 'country' from df1 by comparing df2. The objective is if any one value in df2 is present in df1['frequency'], then I dont want to pick the values from df['country']. For example: If the 'tenor' value is similar to 'frequency' then I dont want the associated 'country' values from df1. I am new to the pandas and picking up fast. Seeking expected output as below. Please suggest.

list = ['EUR.3M','USD.3M','GBP.6M']

Answer 1

IIUC:

s = df1.loc[df1["frequency"].isin(df2["tenor"]),"country"]

print (df1.loc[~df1["country"].isin(s),"country"].unique().tolist())

#['EUR.3M', 'USD.3M', 'GBP.6M']