<p>这对我有效:</p>
<pre><code>import numpy as np
import pandas as pd
dates = np.asarray(pd.date_range('1/1/2000', periods=8))
df1 = pd.DataFrame(np.random.randn(8, 4), index=dates, columns=['A', 'B', 'C', 'D'])
df2 = df1.copy()
df = df1.append(df2)
</code></pre>
<p>收益率:</p>
<pre><code> A B C D
2000-01-01 -0.327208 0.552500 0.862529 0.493109
2000-01-02 1.039844 -2.141089 -0.781609 1.307600
2000-01-03 -0.462831 0.066505 -1.698346 1.123174
2000-01-04 -0.321971 -0.544599 -0.486099 -0.283791
2000-01-05 0.693749 0.544329 -1.606851 0.527733
2000-01-06 -2.461177 -0.339378 -0.236275 0.155569
2000-01-07 -0.597156 0.904511 0.369865 0.862504
2000-01-08 -0.958300 -0.583621 -2.068273 0.539434
2000-01-01 -0.327208 0.552500 0.862529 0.493109
2000-01-02 1.039844 -2.141089 -0.781609 1.307600
2000-01-03 -0.462831 0.066505 -1.698346 1.123174
2000-01-04 -0.321971 -0.544599 -0.486099 -0.283791
2000-01-05 0.693749 0.544329 -1.606851 0.527733
2000-01-06 -2.461177 -0.339378 -0.236275 0.155569
2000-01-07 -0.597156 0.904511 0.369865 0.862504
2000-01-08 -0.958300 -0.583621 -2.068273 0.539434
</code></pre>
<p>如果您还没有使用最新版本的<code>pandas</code>,我强烈建议您升级。现在可以对包含重复索引的数据帧进行操作。</p>