如何使用 pandas 旋转数据框，使可变列变成行？
How to pivot a dataframe with pandas so variable columns become rows?
我目前有以下数据框：
当前 df:
type part number part description waiting period hours
0 service item SOME-X1R-1807 SOME 1 day 24
1 CONSUMABLE RANDOM-462-1171 DESCRIPTION 6 days 144
2 wheel PART-7W-2326 ABOUT THE 7 days 168
3 tyre NUMBER-1R-0762 PARTS FROM THE 8 days 192
4 other NUMBER-XL-0747 PREVIOUS COLUMN 9 days 216
我想旋转 table，并得到以下结果：
预期 df:
SOME-X1R-1807 RANDOM-462-1171 PART-7W-2326 NUMBER-1R-076 NUMBER-XL-0747
part description SOME DESCRIPTION ABOUT THE PARTS FROM THE PREVIOUS COLUMN
type service item CONSUMABLE wheel tyre other
waiting period 1 day 6 days 7 days 8 days 9 days
hours 24 144 168 192 216
问题：
如何旋转数据框以获得此输出？
我尝试过的东西：
我不认为这是关键
df.set_index('part number').T
Out[214]:
part number SOME-X1R-1807 RANDOM-462-1171 PART-7W-2326 \
type service item CONSUMABLE wheel
part description SOME ESCRIPTION ABOUT THE
waiting period 1 day 6 days 7 days
hours 24 144 168
part number NUMBER-1R-0762 NUMBER-XL-0747
type tyre other
part description PARTS FROM THE PREVIOUS COLUMN
waiting period 8 days 9 days
hours 192 216
我目前有以下数据框：
当前 df:
type part number part description waiting period hours
0 service item SOME-X1R-1807 SOME 1 day 24
1 CONSUMABLE RANDOM-462-1171 DESCRIPTION 6 days 144
2 wheel PART-7W-2326 ABOUT THE 7 days 168
3 tyre NUMBER-1R-0762 PARTS FROM THE 8 days 192
4 other NUMBER-XL-0747 PREVIOUS COLUMN 9 days 216
我想旋转 table，并得到以下结果：
预期 df:
SOME-X1R-1807 RANDOM-462-1171 PART-7W-2326 NUMBER-1R-076 NUMBER-XL-0747
part description SOME DESCRIPTION ABOUT THE PARTS FROM THE PREVIOUS COLUMN
type service item CONSUMABLE wheel tyre other
waiting period 1 day 6 days 7 days 8 days 9 days
hours 24 144 168 192 216
问题：
如何旋转数据框以获得此输出？
我尝试过的东西：
我不认为这是关键
df.set_index('part number').T
Out[214]:
part number SOME-X1R-1807 RANDOM-462-1171 PART-7W-2326 \
type service item CONSUMABLE wheel
part description SOME ESCRIPTION ABOUT THE
waiting period 1 day 6 days 7 days
hours 24 144 168
part number NUMBER-1R-0762 NUMBER-XL-0747
type tyre other
part description PARTS FROM THE PREVIOUS COLUMN
waiting period 8 days 9 days
hours 192 216