<p>将<code>DataFrame</code>构造函数与<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.str.get_dummies.html" rel="nofollow noreferrer">^{<cd2>}</a>一起使用:</p>
<pre><code>L = [['1', 'Toy Story (1995)', "Animation|Children's|Comedy"],
['2', 'Jumanji (1995)', "Adventure|Children's|Fantasy"],
['3', 'Grumpier Old Men (1995)', 'Comedy|Romance']]
df = pd.DataFrame(L, columns=['MovieID','Name','Data'])
df1 = df['Data'].str.get_dummies()
print (df1)
Adventure Animation Children's Comedy Fantasy Romance
0 0 1 1 1 0 0
1 1 0 1 0 1 0
2 0 0 0 1 0 1
</code></pre>
<p>对于列<code>Name</code>和<code>Year</code>需要<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.str.split.html" rel="nofollow noreferrer">^{<cd5>}</a>和{a3}来删除尾随<code>)</code>,并且{<cd4>}被转换为<code>int</code>s</p>
^{pr2}$
<p>最后一次删除列<code>Data</code>,并将<code>df1</code>添加到原始列<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.join.html" rel="nofollow noreferrer">^{<cd12>}</a>:</p>
<pre><code>df = df.drop('Data', axis=1).join(df1)
print (df)
MovieID Name Year Adventure Animation Children's Comedy \
0 1 Toy Story 1995 0 1 1 1
1 2 Jumanji 1995 1 0 1 0
2 3 Grumpier Old Men 1995 0 0 0 1
Fantasy Romance
0 0 0
1 1 0
2 0 1
</code></pre>