Question

当我使用计数重新采样某些数据时，我从Series创建了DataFrame 像这样：H2是DataFrame：

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

这产生了一系列如下：

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

索引如下：

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，我有一个DataFrame，第1列为“Date”，第2列为“Sales”（删除索引的第二级）。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

有很多方法可以删除列：

两次致电reset_index()并指定一栏：

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

重置后调用drop()：

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

Answer 2

使用双括号时，例如

H3 = H2[['SOLD_PRICE']]

H3成为DataFrame。如果使用单括号，

H3 = H2['SOLD_PRICE']

然后H3成为一个系列。如果H3是一个系列，那么你想要的结果自然而然：

import pandas as pd
import numpy as np
rng = pd.date_range('1/1/2011', periods=72, freq='M')
H2 = pd.DataFrame(np.arange(len(rng)), index=rng, columns=['SOLD_PRICE'])
H3 = H2['SOLD_PRICE']
H5 = H3.resample('Q', how='count')
H6 = pd.rolling_mean(H5,4)
print(H6.head())

产量

2011-03-31   NaN
2011-06-30   NaN
2011-09-30   NaN
2011-12-31     3
2012-03-31     3
dtype: float64

Pandas重置系列上的索引以删除多索引

2 个答案: