10月12日总结

重塑（Reshaping）

详见多层索引 (opens new window)与重塑 (opens new window)。

#堆叠（Stack）

In [95]: tuples = list(zip(*[['bar', 'bar', 'baz', 'baz',
   ....:                      'foo', 'foo', 'qux', 'qux'],
   ....:                     ['one', 'two', 'one', 'two',
   ....:                      'one', 'two', 'one', 'two']]))
   ....: 

In [96]: index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])

In [97]: df = pd.DataFrame(np.random.randn(8, 2), index=index, columns=['A', 'B'])

In [98]: df2 = df[:4]

In [99]: df2
Out[99]: 
                     A         B
first second                    
bar   one     0.029399 -0.542108
      two     0.282696 -0.087302
baz   one    -1.575170  1.771208
      two     0.816482  1.100230

stack() (opens new window)方法把 DataFrame 列压缩至一层：

In [100]: stacked = df2.stack()

In [101]: stacked
Out[101]: 
first  second   
               B   -0.542108
       two     A    0.282696
               B   -0.087302
baz    one     A   -1.575170
               B    1.771208
       two     A    0.816482
               B    1.100230
dtype: float64

压缩后的 DataFrame 或 Series 具有多层索引， stack() (opens new window)的逆操作是 unstack() (opens new window)，默认为拆叠最后一层：

In [102]: stacked.unstack()
Out[102]: 
                     A         B
first second                    
bar   one     0.029399 -0.542108
      two     0.282696 -0.087302
baz   one    -1.575170  1.771208
      two     0.816482  1.100230

In [103]: stacked.unstack(1)
Out[103]: 
second        one       two
first                      
bar   A  0.029399  0.282696
      B -0.542108 -0.087302
baz   A -1.575170  0.816482
      B  1.771208  1.100230

In [104]: stacked.unstack(0)
Out[104]: 
first          bar       baz
second                      
one    A  0.029399 -1.575170
       B -0.542108  1.771208
two    A  0.282696  0.816482
       B -0.087302  1.100230