<p>我相信您需要<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.get_dummies.html" rel="nofollow noreferrer">^{<cd1>}</a>,如果可能的话,每个列的重复项将删除它们<code>max</code>-对于计数值,输出总是<code>0</code>或<code>1</code>的<code>sum</code>:</p>
<pre><code>df = fl1.cuisines.str.get_dummies(', ').max(level=0, axis=1)
#if need count values
#df = fl1.cuisines.str.get_dummies(', ').sum(level=0, axis=1)
print (df)
Andhra Cafe Chinese Italian Mexican Mughlai North Indian Rajasthani \
0 0 0 1 0 0 1 1 0
1 0 0 1 0 0 0 1 0
2 0 1 0 1 1 0 0 0
3 0 0 0 0 0 0 1 0
4 0 0 0 0 0 0 1 1
5 0 0 0 0 0 0 1 0
6 1 0 1 0 0 0 1 0
South Indian Thai
0 0 0
1 0 1
2 0 0
3 1 0
4 0 0
5 0 0
6 1 0
</code></pre>
<p>使用<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.get_dummies.html" rel="nofollow noreferrer">^{<cd6>}</a>解决方案也有类似的可能性:</p>
<pre><code>df = pd.get_dummies(fl1['cuisines'].str.split(', ',expand=True).stack()).max(level=0)
</code></pre>