擅长:python、mysql、java
<p>我认为<a href="https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.random.choice.html" rel="nofollow noreferrer">np.random.choice</a>如果你想直接取样的话就可以做到:</p>
<pre><code>import numpy as np
# generate some stats (ie your soccer values)
np.random.seed(1)
soccer_stats = np.random.normal(0, 1, size=100)
# sample from them
sampled_stat = np.random.choice(soccer_stats)
print(sampled_stat)
</code></pre>
<blockquote>
<p>-0.8452056414987196</p>
</blockquote>
<p>查看<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html" rel="nofollow noreferrer">np.histogram</a>以观察您从中采样的分布。<a href="https://docs.python.org/2/library/collections.html#collections.Counter" rel="nofollow noreferrer">collections.Counter</a>很适合观察非数字数据的分布(也许是你的足球运动员的名字?)你知道吗</p>