This is a simple example of the problem in hand, if I have the following table
df1
Column1 Column2 Column3
0 cat a 1
1 dog b 4
2 cat b 2
3 bird a 3
4 cat a 2
5 dog b 3
I want to get all the rows that are duplicated regarding Column1 and Column2.
my take on that was as follows:
df1[df1['Column1'].isin(df1[df1[['Column1','Column2']].duplecated()]['Column1]) & df1['Column2'].isin(df1[df1[['Column1','Column2']].duplecated()]['Column2])]
Which have an output of
Column1 Column2 Column3
0 cat a 1
1 dog b 4
2 cat b 2
4 cat a 2
5 dog b 3
While the desired output should be
Column1 Column2 Column3
0 cat a 1
1 dog b 4
4 cat a 2
5 dog b 3
