import pandas as pd
data=pd.read_csv('file.csv', sep=';', decimal=',')
dat=pd.DataFrame(data.T)
for i in dat:
    if dat[dat.columns[i]][1]==dat[dat.columns[i]][2]:
        a=dat.columns[i]

data = pd.read_csv('file.csv', sep=';', decimal=',',  quotechar="'").query('seller != buyer')

data.to_csv('output.csv', index=False)

'id';'seller';'buyer';'timestamp'
1;seller-1;buyer-1;2016-01-01
2;seller-2;buyer-2;2016-01-02
3;same-1;same-1;2016-01-11
4;same-2;same-2;2016-01-22

In [21]: pd.read_csv(r'D:tempbuyer_seller.csv', sep=';')
Out[21]:
   'id'  'seller'  'buyer' 'timestamp'
0     1  seller-1  buyer-1  2016-01-01
1     2  seller-2  buyer-2  2016-01-02
2     3    same-1   same-1  2016-01-11
3     4    same-2   same-2  2016-01-22

In [22]: pd.read_csv(r'D:tempbuyer_seller.csv', sep=';', quotechar="'")
Out[22]:
   id    seller    buyer   timestamp
0   1  seller-1  buyer-1  2016-01-01
1   2  seller-2  buyer-2  2016-01-02
2   3    same-1   same-1  2016-01-11
3   4    same-2   same-2  2016-01-22

In [23]: pd.read_csv(r'D:tempbuyer_seller.csv', sep=';', quotechar="'").query('seller != buyer')
Out[23]:
   id    seller    buyer   timestamp
0   1  seller-1  buyer-1  2016-01-01
1   2  seller-2  buyer-2  2016-01-02

In [27]: df = pd.read_csv(r'D:tempbuyer_seller.csv', sep=';')

In [28]: df.columns.tolist()
Out[28]: ["'id'", "'seller'", "'buyer'", "'timestamp'"]

In [30]: df.columns = df.columns.str.replace("'", '')

In [31]: df.columns.tolist()
Out[31]: ['id', 'seller', 'buyer', 'timestamp']