Pivot_table MultiIndex 到列

Question

我有下表：

In [303]: table.head()
Out[303]: 
            people  weekday  weekofyear
2012-01-01     119        6          52
2012-01-02      76        0           1
2012-01-03      95        1           1
2012-01-04     102        2           1
2012-01-05      87        3           1

我想创建一个简单的pd.DataFrame where :

• columns = [1, 2, ..., 52] (weekofyear)
• rows = [0, 1, ..., 6]（工作日）
• 值 = np.sum

我尝试使用pd.pivot_table，它给了我预期的结果：

In [308]: p = pd.pivot_table(table, index=["weekday"], columns=["weekofyear"], values=["people"], aggfunc=[np.sum])
     ...: p
     ...: 
Out[308]: 
              sum                                             ...             \
           people                                             ...              
weekofyear     1    2    3    4    5    6    7    8   9    10 ...    43   44   
weekday                                                       ...              
0             162   86   84   95   92   98  108  102  97   87 ...   108   86   
1              95  113   88   78  108  112   98  104  87  105 ...    85   82   
2             102   70   93   82  103   80  103   85  82   96 ...    87  105   
3              87   91  101   83   91  100  100   80  89   86 ...    87   91   
4             111   91  110  103   93  116  110   99  78   77 ...    83  102   
5             117  107   99   88   97   90  100   91  97   88 ...   103  110   
6              92   95   90   86   91  103   98  100  89   96 ...    94  101   



weekofyear   45   46   47   48   49   50   51   52  
weekday                                             
0            99   92   99   83  107  106   93  107  
1           105   83  101   93  102   89  113   84  
2            96   84  110   83  104   84   84  116  
3            87   96   87   88   88   83  113   93  
4            93   81  104  108   72  101  109   97  
5            81  107   97   89   86  108  113  101  
6            93   92   93   91   89   96   93  226  

[7 rows x 52 columns]

但是我没有获得我的 weekofyears 列，而是陷入了无法摆脱的 MultiIndex。如下图：

In [309]: p.columns
Out[309]: 
MultiIndex(levels=[['sum'], ['people'], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52]],
           labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51]],
           names=[None, None, 'weekofyear']

虽然索引看起来不错：

In [311]: p.index
Out[311]: Int64Index([0, 1, 2, 3, 4, 5, 6], dtype='int64', name='weekday'  

我尝试使用 unstack() 和 reset_index() 函数，但没有成功。

我错过了什么吗？

Answer 1

不要给values 和aggfunc 提供列表，而应该尝试给它们单独的值。示例 -

p = pd.pivot_table(table, index=["weekday"], columns=["weekofyear"], values="people", aggfunc=np.sum)

---

演示 -

In [3]: table
Out[3]:
            people  weekday  weekofyear
2012-01-01     119        6          52
2012-01-02      76        0           1
2012-01-03      95        1           1
2012-01-04     102        2           1
2012-01-05      87        3           1

In [12]: p = pd.pivot_table(table, index=["weekday"], columns=["weekofyear"], values="people", aggfunc=np.sum)

In [13]: p
Out[13]:
weekofyear   1    52
weekday
0            76  NaN
1            95  NaN
2           102  NaN
3            87  NaN
6           NaN  119

In [14]: p.columns
Out[14]: Int64Index([1, 52], dtype='int64', name='weekofyear')

---

来自documentation -

aggfunc : 函数、默认 numpy.mean 或函数列表
如果传递函数列表，则生成的数据透视表将具有分层列，其顶层是函数名称（从函数对象本身推断）

values 的情况与此类似，但文档中并未具体提及