Here is a dataframe:
test_num file_num dose is_anneal test_name fail
0 10 0 0.00 False test1
1 10 1 10.42 False test1
2 10 2 34.34 False test1
3 10 3 57.06 False test1
4 10 4 103.45 False test1
5 10 5 200.69 False test1
6 10 6 300.24 False test1 8↑
7 11 0 0.00 False test2
8 11 1 10.42 False test2
9 11 2 34.34 False test2
10 11 3 57.06 False test2 2↑
11 11 4 103.45 False test2 2↑
12 11 5 200.69 False test2 2↑
13 11 6 300.24 False test2 2↑,8↑
I want to make a pivot table so that both test_num and test_name could present:
fail_data_pivot = fd.pivot(columns='dose', index=['test_num', 'test_name'], values='fail')
>>ValueError: Wrong number of items passed 14, placement implies 2
fail_data_pivot = fd.pivot_table(columns='dose', index=['test_num', 'test_name'], values='fail')
>>pandas.core.base.DataError: No numeric types to aggregate
If I left only test_num then it works:
fail_data_pivot = fd.pivot(columns='dose', index='test_num', values='fail')
print(fail_data_pivot)
dose 0.00 10.42 34.34 57.06 103.45 200.69 300.24
test_num
10 8↑
11 2↑ 2↑ 2↑ 2↑,8↑
This is what I want instead:
dose 0.00 10.42 34.34 57.06 103.45 200.69 300.24
test_num test_name
10 test1 8↑
11 test2 2↑ 2↑ 2↑ 2↑,8↑
How to make a pivot table with multiple index?
