<p>不要分解值,如果需要以相同的方式处理每一列,最好将<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.get_dummies.html" rel="nofollow noreferrer">^{<cd1>}</a>与<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html" rel="nofollow noreferrer">^{<cd2>}</a>一起使用:</p>
<pre><code>df = pd.DataFrame({'Q1': ['A,B', 'A,C', 'A,B', 'B,C', 'A,B,C','C,B,A','B,C,A'],
'Q2': ['B,A', 'C,A', 'B,C,A', 'A,B', 'A,C', 'B,C','C,B'],
'Q3': ['C,A', 'C,B', 'A,B', 'C,B', 'A,B,C','A,B,C','C,A']})
df = pd.concat([df[x].str.get_dummies(',') for x in df], keys=df.columns, axis=1)
df.columns = df.columns.map('_'.join)
print (df)
Q1_A Q1_B Q1_C Q2_A Q2_B Q2_C Q3_A Q3_B Q3_C
0 1 1 0 1 1 0 1 0 1
1 1 0 1 1 0 1 0 1 1
2 1 1 0 1 1 1 1 1 0
3 0 1 1 1 1 0 0 1 1
4 1 1 1 1 0 1 1 1 1
5 1 1 1 0 1 1 1 1 1
6 1 1 1 0 1 1 1 0 1
</code></pre>
<p>如果希望每列分隔数据帧:</p>
<pre><code>df1 = df['Q1'].str.get_dummies(',')
print (df1)
A B C
0 1 1 0
1 1 0 1
2 1 1 0
3 0 1 1
4 1 1 1
5 1 1 1
6 1 1 1
</code></pre>