从退出的列名中在Pandas DataFrame中创建一个新列

Question

我想解构一个pandas DataFrame，使用列标题作为一个新的数据列，并创建一个包含行索引和列的所有组合的列表。比解释更容易展示的：

index_col = ["store1", "store2", "store3"]
cols = ["January", "February", "March"]
values = [[2,3,4],[5,6,7],[8,9,10]]
df = pd.DataFrame(values, index=index_col, columns=cols)

[['store1', 'January', 2],
 ['store1', 'February', 3],
 ['store1', 'March', 4],
 ['store2', 'January', 5],
 ['store2', 'February', 6],
 ['store2', 'March', 7],
 ['store3', 'January', 8],
 ['store3', 'February', 9],
 ['store3', 'March', 10]]

Answer 1

我更喜欢叠而不是拆，然后交换层次：

>>> df.stack().reset_index().to_numpy()
array([['store1', 'January', 2],
       ['store1', 'February', 3],
       ['store1', 'March', 4],
       ['store2', 'January', 5],
       ['store2', 'February', 6],
       ['store2', 'March', 7],
       ['store3', 'January', 8],
       ['store3', 'February', 9],
       ['store3', 'March', 10]], dtype=object)
>>> 

或者使用melt和ignore_index=false:

>>> df.melt(ignore_index=False).reset_index().to_numpy()
array([['store1', 'January', 2],
       ['store2', 'January', 5],
       ['store3', 'January', 8],
       ['store1', 'February', 3],
       ['store2', 'February', 6],
       ['store3', 'February', 9],
       ['store1', 'March', 4],
       ['store2', 'March', 7],
       ['store3', 'March', 10]], dtype=object)
>>>