Correct way of merging two CSV files without duplicates based on a column in Python

I want to merget 2 CSV files into one CSV and remove all duplicated rows based on a column (second column).

Here is my first CSV file:

    Skufnoo,748702985,-6026769894509215039,ВупÑеньпупÑеньâ¤ï¸â€ðŸ©¹ðŸ’—,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,4,True,False,0    mAtkmb,5213786988,4161254730445748607,ДаниÑльБлинов,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,False,False,False,0    sheluvjoseph,1421438213,8544915453690665435,អនសំអុល,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,5,True,False,0

Second CSV file:

    cchamnap,748702985,-7259273529368744780,Chim,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,5,True,False,0    chhounkha,765670208,3636141294788837002,Chhuon Sokha,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,False,False,False,0    CHHORMNIMOL8,5213786988,5104468652588260401,ឌីណា.,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,5,True,False,0    Chhailin17,1133044248,6931066845789435875,Chhai Lin,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,5,True,False,0

Output file (own_updated2.csv) should be:

    Skufnoo,748702985,-6026769894509215039,ВупÑеньпупÑеньâ¤ï¸â€ðŸ©¹ðŸ’—,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,4,True,False,0    mAtkmb,5213786988,4161254730445748607,ДаниÑльБлинов,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,False,False,False,0    sheluvjoseph,1421438213,8544915453690665435,អនសំអុល,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,5,True,False,0    chhounkha,765670208,3636141294788837002,Chhuon Sokha,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,False,False,False,0    Chhailin17,1133044248,6931066845789435875,Chhai Lin,AA2888 ចាក់បាល់និងកាសុីណូអនឡាញ (070645555),1746008070,False,False,5,True,False,0

I have tried the following codes:

    import pandas as pd    import csv    df1 = pd.read_csv("own1.csv")    df2 = pd.read_csv("own2.csv")    merged = pd.concat([df1,df2])    with open('own_updated.csv', 'w', newline="", encoding='utf-8') as nf:        merged.to_csv(nf, index=False)    with open('own_updated.csv', 'r', encoding="utf8") as in_file, open('own_updated2.csv', 'w', newline="", encoding="utf8") as out_file:        in_data = csv.reader(in_file, delimiter=',')        writer=csv.writer(out_file)        tracks = set()          # Tracking duplicates of the second column's cell        for row in in_data:            key = row[1]            if key not in tracks:                writer.writerow(row)                tracks.add(key)

It works well. But the problem is there is an extra file which is not needed own_updated.csv. How can I store all data from merging two CSV files without creating a file which is own_updated.csv, i.e. store them in a memory, then process the removal of duplicates based on the second column?