1. import pandas as pd
2. import itertools
3.  
4. filepath = 'ADR4.dat'
5.  
6. vector = []
7. col_name = ['u', 'u_e', 'g', 'g_e', 'r', 'r_e', 'i', 'i_e', 'z', 'z_e', 'name']
8.  
9. columns_to_use = [35] + list(range(19, 29))  
10. data = pd.read_csv(filepath, sep="\\s+", usecols=columns_to_use, header=None, names=col_name)
11.  
12. filtered_data = data.loc[data['name'] != '-']
13. sorted_data = filtered_data.sort_values(by='name')
14.  
15. merged_99_99 = pd.concat([sorted_data[['u', 'g', 'r', 'i', 'z']] == 99.99, sorted_data['name']], axis=1)
16. merged_9_99 = pd.concat([sorted_data[['u_e', 'g_e', 'r_e', 'i_e', 'z_e']] == 9.99, sorted_data['name']], axis=1)
17.  
18.  
19. counts_99_99 = {}
20. counts_9_99 = {}
21.  
22. for filter_number in range(2, 6):
23.     for combination in itertools.combinations(['u', 'g', 'r', 'i', 'z'], filter_number):
24.         count_true = (merged_99_99[list(combination)] == True).any(axis=1).sum()
25.         counts_99_99[combination] = len(merged_99_99) - count_true
26.     for combination in itertools.combinations(['u_e', 'g_e', 'r_e', 'i_e', 'z_e'], filter_number):
27.         count_true = (merged_9_99[list(combination)] == True).any(axis=1).sum()
28.         counts_9_99[combination] = len(merged_9_99) - count_true
29.  
30. print(counts_99_99, '\n', counts_9_99)
31.  
32.