python - 使用 Pandas 将数据框中的多列转换为两个新列

Question

我在 python pandas 环境中工作:D
目前，我有一个如下所示的数据框:

 0   1   2   3   4   5   6   7   8   9   10   11   12   13   14   15   16   17   18
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8 ex9 ex10 ex11 ex12 ex13 ex14 ex15 ex16 ex17 ex18 

我的目标是使数据框看起来像这样:

 0   1   2   3   4   5  6    7   8   category   amount   
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     9        ex9
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     10       ex10
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     11       ex11
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     12       ex12
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     13       ex13
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     14       ex14
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     15       ex15
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     16       ex16
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     17       ex17
ex0 ex1 ex2 ex3 ex4 ex5 ex6 ex7 ex8     18       ex18

基本上，我希望最后 9 列标题和值在 2 个新列上成为它们自己的行，同时保持前 8 列和行相同。我知道这意味着数据将被复制。
我在 stackoverflow 上看到了一些其他答案，将以下代码用于较小的数据帧，但它对我不起作用:

df.melt(['Type', 'Class'], var_name='Date', value_name='Value')

(df.set_index(['Type', 'Class'])
   .stack()
   .rename_axis(['Type', 'Class', 'Date'])
   .reset_index(name='Value')
)

任何和所有的帮助表示赞赏!
谢谢

Answer 1

你快到了 melt

df.melt(id_vars=df.columns[:9], var_name='category', value_name='amount')

Out[469]:
     0    1    2    3    4    5    6    7    8 category amount
0  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8        9    ex9
1  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       10   ex10
2  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       11   ex11
3  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       12   ex12
4  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       13   ex13
5  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       14   ex14
6  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       15   ex15
7  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       16   ex16
8  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       17   ex17
9  ex0  ex1  ex2  ex3  ex4  ex5  ex6  ex7  ex8       18   ex18