Python 熊猫透视表&x2B；保留另外两列

我正在尝试改变这个df：

data = {
    'account': ['Account 1', 'Account 1', 'Account 1', 'Account 1', 'Account 1', 'Account 2'],
    'product': ['Product 1', 'Product 1', 'Product 1', 'Product 2', 'Product 3', 'Product 1'],
    'metric': ['Meric 1', 'Meric 1', 'Meric 2', 'Meric 1', 'Meric 1', 'Meric 1'],
    'date': ['Date 1', 'Date 2', 'Date 3', 'Date 4', 'Date 5', 'Date 1'],
    'value': [1, 2, 3, 4, 5, 6]
}

pd.DataFrame(data)

     account    product   metric    date  value
0  Account 1  Product 1  Meric 1  Date 1      1
1  Account 1  Product 1  Meric 1  Date 2      2
2  Account 1  Product 1  Meric 2  Date 3      3
3  Account 1  Product 2  Meric 1  Date 4      4
4  Account 1  Product 3  Meric 1  Date 5      5
5  Account 2  Product 1  Meric 1  Date 1      6

像这样进入视图，但按原样添加日期和产品列

new.pivot_table(index='account', columns='metric', values='value')

到目前为止我所拥有的：

metric     Meric 1  Meric 2
account                    
Account 1      3.0      3.0
Account 2      6.0      NaN

metric     Meric 1  Meric 2 product  date
account                    
Account 1      1.0      Nan Product 1 Date 1
Account 1      2.0      Nan Product 1 Date 2
Account 1      Nan      3   Product 1 Date 3
...

我在找什么：

metric     Meric 1  Meric 2
account                    
Account 1      3.0      3.0
Account 2      6.0      NaN

metric     Meric 1  Meric 2 product  date
account                    
Account 1      1.0      Nan Product 1 Date 1
Account 1      2.0      Nan Product 1 Date 2
Account 1      Nan      3   Product 1 Date 3
...

---

唯一的问题是帐户将被重复，但这正是我想要的-如果我们有不同日期的相同产品。

将两列添加到

pivot_table

中的参数

索引中，然后将第二级和第三级转换为列，并更改列的顺序：

df = (new.pivot_table(index=['account','product','date'], columns='metric', values='value')
         .reset_index(level=[1,2]))
df = df[df.columns[2:].tolist() + df.columns[:2].tolist()]

print (df)
metric     Meric 1  Meric 2    product    date
account                                       
Account 1      1.0      NaN  Product 1  Date 1
Account 1      2.0      NaN  Product 1  Date 2
Account 1      NaN      3.0  Product 1  Date 3
Account 1      4.0      NaN  Product 2  Date 4
Account 1      5.0      NaN  Product 3  Date 5
Account 2      6.0      NaN  Product 1  Date 1

你能用实际值替换xxx吗？@jezrael用实际值更新了预期视图非常感谢！我不知道我怎么会错过将这些键添加到索引中。。