擅长:python、mysql、java
<p>您可以通过将整个df与字符串进行比较来创建一个布尔掩码,并调用<code>dropna</code>passing param<code>how='all'</code>删除字符串未出现在所有列中的行:</p>
<pre><code>In [59]:
df[df == 'banana'].dropna(how='all')
Out[59]:
A B C
1 NaN banana NaN
3 banana NaN NaN
</code></pre>
<p>要测试多个值,可以使用多个遮罩:</p>
<pre><code>In [90]:
banana = df[(df=='banana')].dropna(how='all')
banana
Out[90]:
A B C
1 NaN banana NaN
3 banana NaN NaN
In [91]:
apple = df[(df=='apple')].dropna(how='all')
apple
Out[91]:
A B C
1 apple NaN NaN
2 NaN NaN apple
4 apple apple NaN
</code></pre>
<p>您可以使用<code>index.intersection</code>仅为常用索引值编制索引:</p>
<pre><code>In [93]:
df.loc[apple.index.intersection(banana.index)]
Out[93]:
A B C
1 apple banana pear
</code></pre>