具有 3 级多索引的 Pandas 数据透视表

Question

我已经尝试了一切可以想象的方法来获取这个数据框

import pandas as pd

dataDict = {'State': ['Idaho', 'Wyoming', 'Montana', 'Idaho', 'Idaho', 'Wyoming', 'Montana', 'Idaho', 'Idaho', 'Wyoming', 'Montana', 'Idaho'],
            'City': ['Boise', 'Jackson', 'Missoula', 'Sandpoint', 'Boise', 'Jackson', 'Missoula', 'Sandpoint', 'Boise', 'Jackson', 'Missoula', 'Sandpoint'],
            'Years': [2010, 2010, 2010, 2010, 2011, 2011, 2011, 2011, 2012, 2012, 2012, 2012],
            'PizzaOrdered' : [3000, 50, 1000, 78, 3250, 75, 1250, 82, 4000, 98, 4100, 92],
            'TacosOrdered' : [5000, 65, 1900, 88, 5780, 78, 2128, 90, 6125, 87, 5999, 95]
            }
testData = pd.DataFrame(data=dataDict)

并将其转换为这样

我尝试过pivot、groupby、set_index、stacking、unstacking，我可以接近但不安静我在下面提供的这个例子

Answer 1

在unstack之前需要melt

df_final = (testData.melt(['State', 'City', 'Years'], var_name='Ordered')
                    .set_index(['State', 'City', 'Ordered', 'Years'])['value']
                    .unstack())

Out[54]:
Years                           2010  2011  2012
State   City      Ordered
Idaho   Boise     PizzaOrdered  3000  3250  4000
                  TacosOrdered  5000  5780  6125
        Sandpoint PizzaOrdered    78    82    92
                  TacosOrdered    88    90    95
Montana Missoula  PizzaOrdered  1000  1250  4100
                  TacosOrdered  1900  2128  5999
Wyoming Jackson   PizzaOrdered    50    75    98
                  TacosOrdered    65    78    87