<p>另一种方法:</p>
<pre><code>a
0 United Kingdom - ��Global Consumer Technolog...
1 United Kingdom - ��VP Technology - Founder -...
2 Aberdeen - ��SeniorCore Analysis Specialist ...
3 London, - ��ED, Equit Technology, London - �...
4 United Kingdom - ��Chief Officer, Group Tech...
</code></pre>
<p>使用此函数可以使用<a href="https://docs.python.org/2/library/functions.html#ord" rel="nofollow noreferrer">ord</a>内置函数提取assci char(其中Unicode码位优于128)</p>
<pre><code>def extract_ascii(x):
string_list = filter(lambda y : ord(y) < 128, x)
return ''.join(string_list)
</code></pre>
<p>并将其应用于列。你知道吗</p>
<pre><code>df1.a.apply(extract_ascii).str.split('-', expand=True)
</code></pre>
<p>结果如下:</p>
<pre><code> 0 1 2 3
0 United Kingdom Global Consumer Technology American Express None
1 United Kingdom VP Technology Founder Hogarth Worldwide
2 Aberdeen SeniorCore Analysis Specialist COREX Group None
3 London, ED, Equit Technology, London Morgan Stanley None
4 United Kingdom Chief Officer, Group Technology BP None
</code></pre>