adding a second conditional statement to an 'if' statement based on the value in a different dataframe column

I currently have the following conditional:

if not tops_subset.eq(row.iloc[2:4]).all(axis=1).any():

For some background, it is from this code block:

tops_df = pd.read_csv('tops.csv', header=None)tops_subset = tops_df.iloc[:, 2:4]rows_written = 0with open('for_email.csv', 'w', newline='') as for_email_file:    for index, row in df_sorted_no_duplicates.iterrows():        # Check if the third and fourth columns of the current row exist in 'tops.csv'        if not tops_subset.eq(row.iloc[2:4]).all(axis=1).any():

It correctly checks if data in two columns already exist in any row of the file tops.csv

I want to modify if so that it accommodates a second condition. The second condition is that tops_subset.eq(row.iloc[2:4]).all(axis=1).any() is true AND the value in the second from last column in the row in tops.csv where the data exist is 0.

To be clear, I want the if statement to accept either:

1. The one it is already accepting which has the not statement

OR

2. The condition I described above

I am having trouble checking if the row where the data exists has a 0 in the second from last column. This is where I need help.

I have tried this:

if (tops_subset.eq(row.iloc[2:4]).all(axis=1).any() and tops_subset.iloc[:, -2].eq(0).any()) or not tops_subset.eq(row.iloc[2:4]).all(axis=1).any():

and this:

if (tops_subset.eq(row.iloc[2:4]).all(axis=1).any() and tops_subset.loc[tops_subset.eq(row.iloc[2:4]).all(axis=1), int(tops_subset.columns[-2])].eq(0).any()) or not tops_subset.eq(row.iloc[2:4]).all(axis=1).any():

Both don't work.