如何分组和转动（？）数据框

Question

我的数据框看起来像这样：

ID  Species Count
1   Pine    1000
1   Spruce  1000
2   Pine    2000
3   Pine    1000
3   Spruce  500
3   Birch   500

我想要的是：

    Pine    Spruce  Birch
ID  Count   Count   Count
1   1000    1000    
2   2000        
3   1000    500 500

所以即时尝试：

a = df.groupby(['ID']).cumcount().astype(str)
newdf = df.set_index(['ID', a]).unstack(fill_value=0).sort_index(level=1, axis=1)

这给了我：

ID  Count   Species Count   Species Count   Species
1   1000    Pine    1000    Spruce      
2   2000    Pine                
3   1000    Pine    500     Spruce  500 Spruce

我该如何解决这个问题？

Answer 1

简单pivot

df.pivot('ID','Species','Count')
Out[493]: 
Species  Birch    Pine  Spruce
ID                            
1          NaN  1000.0  1000.0
2          NaN  2000.0     NaN
3        500.0  1000.0   500.0

Answer 2

In [94]: df.set_index(['ID', 'Species'])['Count'].unstack(fill_value=0)
Out[94]:
Species  Birch  Pine  Spruce
ID
1            0  1000    1000
2            0  2000       0
3          500  1000     500