擅长:python、mysql、java
<p>如果性能很重要,请使用<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.cumprod.html" rel="nofollow noreferrer">^{<cd1>}</a>:</p>
<pre><code>np.cumprod(1 + df['Daily_rets'].values) - 1
</code></pre>
<p><strong>计时</strong>:</p>
<pre><code>#7k rows
df = pd.concat([df] * 1000, ignore_index=True)
In [191]: %timeit np.cumprod(1 + df['Daily_rets'].values) - 1
41 µs ± 282 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
In [192]: %timeit (1 + df.Daily_rets).cumprod() - 1
554 µs ± 3.63 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
</code></pre>