<p>使用以下数据帧:</p>
<pre><code>df = pd.DataFrame({
'Genre': ['Romance', 'Tech', 'Romance', 'Comedy', 'Tech', 'Comedy', 'Romance', 'Romance',],
'Gender': ['Male', 'Male', 'Male', 'Female', 'Female', 'Male', 'Female', 'Male',]})
</code></pre>
<p>为计数添加一个额外的列:</p>
<pre><code>df['value'] = 1
</code></pre>
<p>这将为您提供:</p>
<pre><code> Genre Gender value
0 Romance Male 1
1 Tech Male 1
2 Romance Male 1
3 Comedy Female 1
4 Tech Female 1
5 Comedy Male 1
6 Romance Female 1
7 Romance Male 1
</code></pre>
<p>然后根据两个字段“类型”和“性别”进行分组,并获得计数:</p>
<pre><code>counts = df.groupby(['Genre', 'Gender']).count()
</code></pre>
<p>产出:</p>
<pre><code> value
Genre Gender
Comedy Female 1
Male 1
Romance Female 1
Male 3
Tech Female 1
Male 1
</code></pre>
<p>您可以排序:</p>
<pre><code>sorted = counts.sort_values(by='value', ascending=False)
</code></pre>
<p>并绘制:</p>
<pre><code>sorted.plot(kind='bar', figsize=(15,8))
</code></pre>
<p>将为您提供:</p>
<p><a href="https://i.stack.imgur.com/kBl1R.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/kBl1R.png" alt="enter image description here"/></a></p>