只需致电reset_index()：
In [130]: s
Out[130]:
0 1
1999-03-31 SOLD_PRICE NaN
1999-06-30 SOLD_PRICE NaN
1999-09-30 SOLD_PRICE NaN
1999-12-31 SOLD_PRICE 3
2000-03-31 SOLD_PRICE 3
Name: 2, dtype: float64
In [131]: s.reset_index()
Out[131]:
0 1 2
0 1999-03-31 SOLD_PRICE NaN
1 1999-06-30 SOLD_PRICE NaN
2 1999-09-30 SOLD_PRICE NaN
3 1999-12-31 SOLD_PRICE 3
4 2000-03-31 SOLD_PRICE 3
调用reset_index()两次并指定一列：
In [136]: s.reset_index(0).reset_index(drop=True)
Out[136]:
0 2
0 1999-03-31 NaN
1 1999-06-30 NaN
2 1999-09-30 NaN
3 1999-12-31 3
4 2000-03-31 3
重置索引后删除列：
In [137]: df = s.reset_index()
In [138]: df
Out[138]:
0 1 2
0 1999-03-31 SOLD_PRICE NaN
1 1999-06-30 SOLD_PRICE NaN
2 1999-09-30 SOLD_PRICE NaN
3 1999-12-31 SOLD_PRICE 3
4 2000-03-31 SOLD_PRICE 3
In [139]: del df[1]
In [140]: df
Out[140]:
0 2
0 1999-03-31 NaN
1 1999-06-30 NaN
2 1999-09-30 NaN
3 1999-12-31 3
4 2000-03-31 3
drop()重置后致电：
In [144]: s.reset_index().drop(1, axis=1)
Out[144]:
0 2
0 1999-03-31 NaN
1 1999-06-30 NaN
2 1999-09-30 NaN
3 1999-12-31 3
4 2000-03-31 3
然后，在重置索引后，只需重命名列
In [146]: df.columns = ['Date', 'Sales']
In [147]: df
Out[147]:
Date Sales
0 1999-03-31 NaN
1 1999-06-30 NaN
2 1999-09-30 NaN
3 1999-12-31 3
4 2000-03-31 3
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