熊猫在系列上重置索引以删除多索引

Question

我创建了一个Series从DataFrame，当我重新采样一些数据，象这样一个数：其中H2是DataFrame：

H3=H2[['SOLD_PRICE']]
H5=H3.resample('Q',how='count')
H6=pd.rolling_mean(H5,4)

这产生了一个看起来像这样的系列：

1999-03-31  SOLD_PRICE     NaN
1999-06-30  SOLD_PRICE     NaN
1999-09-30  SOLD_PRICE     NaN
1999-12-31  SOLD_PRICE    3.00
2000-03-31  SOLD_PRICE    3.00

索引看起来像：

MultiIndex
[(1999-03-31 00:00:00, u'SOLD_PRICE'), (1999-06-30 00:00:00, u'SOLD_PRICE'), (1999-09-30 00:00:00, u'SOLD_PRICE'), (1999-12-31 00:00:00, u'SOLD_PRICE'),.....

我不希望第二列作为索引。理想情况下，我将第DataFrame1列作为“日期”，将第2列作为“销售”（删除索引的第二层）。我不太清楚如何重新配置​​索引。

Answer 1

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

有多种删除列的方法：

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