<p>对于那些想知道题目的搜索:</p>
<blockquote>
<p>Check if all columns in rows value is NaN</p>
</blockquote>
<p>一个简单的方法是:</p>
<pre><code>df[[list_of_cols_to_check]].isnull().apply(lambda x: all(x), axis=1)
</code></pre>
<hr/>
<pre><code>import pandas as pd
import numpy as np
df = pd.DataFrame({'movie': [np.nan, 'thg', 'mol', 'mol', 'lob', 'lob'],
'rating': [np.nan, 4., 5., np.nan, np.nan, np.nan],
'name': ['John', np.nan, 'N/A', 'Graham', np.nan, np.nan]})
df.head()
</code></pre>
<p><a href="https://i.stack.imgur.com/On8y8.png" rel="noreferrer"><img src="https://i.stack.imgur.com/On8y8.png" alt="enter image description here"/></a></p>
<hr/>
<p>要检查所有列是否为NaN:</p>
<pre><code>cols_to_check = df.columns
df['is_na'] = df[cols_to_check].isnull().apply(lambda x: all(x), axis=1)
df.head()
</code></pre>
<p><a href="https://i.stack.imgur.com/21meZ.png" rel="noreferrer"><img src="https://i.stack.imgur.com/21meZ.png" alt="enter image description here"/></a></p>
<hr/>
<p>要检查列“name”、“rating”是否为NaN,请执行以下操作:</p>
<pre><code>cols_to_check = ['name', 'rating']
df['is_na'] = df[cols_to_check].isnull().apply(lambda x: all(x), axis=1)
df.head()
</code></pre>
<p><a href="https://i.stack.imgur.com/WErgC.png" rel="noreferrer"><img src="https://i.stack.imgur.com/WErgC.png" alt="enter image description here"/></a></p>