擅长:python、mysql、java
<p>您可以尝试使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.apply.html" rel="nofollow">^{<cd1>}</a><code>Series</code>创建{<cd3>},然后<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.stack.html" rel="nofollow">^{<cd4>}</a>和{a3}。最后一个可能的过滤器顶值是按<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.head.html" rel="nofollow">^{<cd6>}</a>或<code>[:5]</code>:</p>
<pre><code>print df
a
0 [hhcb, hcbc, cbcc, bccc, cccd, ccdd, cddh]
1 [fahb, ahba, hbac, bacc]
2 [hchc, chcb, hcbh]
3 [hhhh, hhhh, hhhc, hhcd, hcdc, cdcc]
4 [habb, abbb, bbbb, bbbc, bbcc, bccd, ccdh, cdhd]
print df.a.apply(pd.Series).stack().value_counts()[:1]
hhhh 2
dtype: int64
</code></pre>
<p>编辑:</p>
<p>如果您需要在每一行中使用top <code>5</code>,请使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.drop_duplicates.html" rel="nofollow">^{<cd9>}</a>:</p>
^{pr2}$