filter dataframe based on 2 conditions

I have following example dataframe:

df = pandas.DataFrame({'col1': [A, A, B, A, B, B, A, B, B, A], 'col2': [0, 0, 1, 1, 0, 1, 0, 0, 0, 0]})

Now, I would like to create a second dataframe containing only the rows from df where:
col1 – A matches col2: 0 and
col1 – B matches col2: 1

df2 = pandasDataFrame({'col1' : [A, A, B, B, A, A], 'col2' : [0, 0, 1, 1, 0, 0]})

I have tried with query, but it is only working on one condition, if I separate condition pair in paranthesis, I get an empty dataframe.

Thank you in advance for your help!

>Solution :

You could use create a boolean mask and filter:

out = df[(df['col1'].eq('A')&df['col2'].eq(0)) | (df['col1'].eq('B') & df['col2'].eq(1))]

Output:

  col1  col2
0    A     0
1    A     0
2    B     1
5    B     1
6    A     0
9    A     0