How to remove rows using another dataframe

October 19, 2022

I have a dataframe where I have my complete dataset, it has 4 columns, but I need to remove all rows that have the customer_id from another dataframe

Here’s an example:

df1 = pd.DataFrame({'client_id' : ['123456', '451245', '563234', '753214', '412456', '442312', '123411', '987654'],
                'name_fran' : [    'will',     'bruce',     'john',     'jorge',     'well',     'dani',     'rafa',     'manoel'],
                'id_fran' : ['331'  ,   '221',   '312',   '531',   '678',   '214',   '456',   '886']})

df2 = pd.DataFrame({'client_id' : ['123456', '987654']})

df1 :

index	client_id	name_fran	id_fran
0	123456	will	331
1	451245	bruce	221
2	563234	john	312
3	753214	jorge	531
4	412456	well	678
5	442312	dani	214
6	123411	rafa	456
7	987654	manoel	886

df2:

index	client_id
0	123456
1	987654

result I need is this:

index	client_id	name_fran	id_fran
0	451245	bruce	221
1	563234	john	312
2	753214	jorge	531
3	412456	well	678
4	442312	dani	214
5	123411	rafa	456

I’ve tried a few ways but got no results, what’s the best way to do this?

>Solution :

We could do isin

df1 = df1.loc[~df1['client_id'].isin(df2['client_id'])].reset_index(drop=True)
df1
Out[278]: 
  client_id name_fran id_fran
0    451245     bruce     221
1    563234      john     312
2    753214     jorge     531
3    412456      well     678
4    442312      dani     214
5    123411      rafa     456