Python 如何防止索引旋转？
我有一个数据帧（fx_return）： 创建索引 现在我们必须创建索引Python 如何防止索引旋转？,python,pandas,dataframe,pivot,reshape,Python,Pandas,Dataframe,Pivot,Reshape,我有一个数据帧（fx_return）： 创建索引 现在我们必须创建索引 fx_return.set_index('index_date', drop=True, append=False, inplace=False, verify_integrity=False) 透视数据 重新调整数据形状： 有没有办法保存索引？ 索引丢失了，有没有办法保存它 与熔体一起使用： print (fx_return.stack().reset_index(name='val')) index_date
fx_return.set_index('index_date', drop=True, append=False, inplace=False, verify_integrity=False)
print (fx_return.stack().reset_index(name='val'))
index_date ccy val
0 2016-06-01 CHF 1.013017
1 2016-06-01 EUR 1.117800
2 2016-06-01 GBP 1.442550
3 2016-06-01 USD 1.000000
4 2016-06-02 CHF 1.010560
5 2016-06-02 EUR 1.116150
6 2016-06-02 GBP 1.444150
7 2016-06-02 USD 1.000000
8 2016-06-03 CHF 1.022547
9 2016-06-03 EUR 1.132600
10 2016-06-03 GBP 1.455300
11 2016-06-03 USD 1.000000
12 2016-06-06 CHF 1.027749
13 2016-06-06 EUR 1.135050
14 2016-06-06 GBP 1.442800
15 2016-06-06 USD 1.000000
16 2016-06-07 CHF 1.034661
17 2016-06-07 EUR 1.135850
18 2016-06-07 GBP 1.457250
19 2016-06-07 USD 1.000000
20 2016-06-08 CHF 1.042318
21 2016-06-08 EUR 1.140400
22 2016-06-08 GBP 1.456700
23 2016-06-08 USD 1.000000
24 2016-06-09 CHF 1.038691
25 2016-06-09 EUR 1.132400
26 2016-06-09 GBP 1.447200
27 2016-06-09 USD 1.000000
28 2016-06-10 CHF 1.037129
29 2016-06-10 EUR 1.128900
30 2016-06-10 GBP 1.434650
31 2016-06-10 USD 1.000000
fx_return = fx_return.pivot(index='index_date', columns='ccy', values='rate')
ccy CHF EUR GBP USD
index_date
2016-06-01 1.013017 1.11780 1.44255 1.0
2016-06-02 1.010560 1.11615 1.44415 1.0
2016-06-03 1.022547 1.13260 1.45530 1.0
2016-06-06 1.027749 1.13505 1.44280 1.0
2016-06-07 1.034661 1.13585 1.45725 1.0
2016-06-08 1.042318 1.14040 1.45670 1.0
2016-06-09 1.038691 1.13240 1.44720 1.0
2016-06-10 1.037129 1.12890 1.43465 1.0
fx_return = pd.melt(fx_return, col_level=0)
ccy value
0 CHF 1.013017
1 CHF 1.010560
2 CHF 1.022547
3 CHF 1.027749
4 CHF 1.034661
print (fx_return.stack().reset_index(name='val'))
index_date ccy val
0 2016-06-01 CHF 1.013017
1 2016-06-01 EUR 1.117800
2 2016-06-01 GBP 1.442550
3 2016-06-01 USD 1.000000
4 2016-06-02 CHF 1.010560
5 2016-06-02 EUR 1.116150
6 2016-06-02 GBP 1.444150
7 2016-06-02 USD 1.000000
8 2016-06-03 CHF 1.022547
9 2016-06-03 EUR 1.132600
10 2016-06-03 GBP 1.455300
11 2016-06-03 USD 1.000000
12 2016-06-06 CHF 1.027749
13 2016-06-06 EUR 1.135050
14 2016-06-06 GBP 1.442800
15 2016-06-06 USD 1.000000
16 2016-06-07 CHF 1.034661
17 2016-06-07 EUR 1.135850
18 2016-06-07 GBP 1.457250
19 2016-06-07 USD 1.000000
20 2016-06-08 CHF 1.042318
21 2016-06-08 EUR 1.140400
22 2016-06-08 GBP 1.456700
23 2016-06-08 USD 1.000000
24 2016-06-09 CHF 1.038691
25 2016-06-09 EUR 1.132400
26 2016-06-09 GBP 1.447200
27 2016-06-09 USD 1.000000
28 2016-06-10 CHF 1.037129
29 2016-06-10 EUR 1.128900
30 2016-06-10 GBP 1.434650
31 2016-06-10 USD 1.000000