How to work with ' df.loc ' so that it combines two columns to return ' unique ' values?

I ran into a problem to be able to combine two columns before generating a unique list.

CSV file:

country,half,uniqueTournament
Brazil,1st half,Serie A
England,1st half,Championship
Argentina,2nd half,Primera Liga
Brazil,1st half,Serie A

My attempt:

import pandas as pd

csv_file = '@@@@@@@@@@@@@'
df = pd.read_csv(csv_file)

df.loc[(df['half'] == '1st half'), 'country' + ' - ' + 'uniqueTournament'].unique()

Expected outcome:

Brazil - Serie A
England - Championship

>Solution :

If df was like:

     country      half uniqueTournament
0     Brazil  1st half          Serie A
1    England  1st half     Championship
2  Argentina  1st half     Primera Liga
3     Brazil  1st half          Serie A
4     Brazil  2nd half          Serie A

then you could create a new column, then groupby + agg(list):

df['new'] = df['country'] + ' - '+ df['uniqueTournament']
df.drop_duplicates(subset=['half','new']).groupby('half')['new'].agg(list).tolist()

or you could use groupby + unique:

out = df.groupby('half')['new'].unique().tolist()

Output:

[['Brazil - Serie A', 'England - Championship', 'Argentina - Primera Liga'],
 ['Brazil - Serie A']]