<h2>使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html" rel="nofollow noreferrer">^{<cd1>}</a>:</h2>
<h3>数据:</h3>
<pre class="lang-py prettyprint-override"><code> Date ID Calendar_Year Month Dayname AAA_1E AAA_BMITH AAA_4.1 AAA_CH
2019-09-17 8661 2019 Jan Sun NaN NaN NaN NaN
2019-09-18 8662 2019 Jan Sun 1.0 3.0 34.0 1.0
2019-09-19 8663 2019 Jan Sun NaN NaN NaN NaN
2019-09-20 8664 2019 Jan Mon NaN NaN NaN NaN
2019-09-20 8664 2019 Jan Mon 2.0 4.0 32.0 3.0
2019-09-20 8664 2019 Jan Sat NaN NaN NaN NaN
2019-09-20 8664 2019 Jan Sat NaN NaN NaN NaN
2019-09-20 8664 2019 Jan Sat 0.0 4.0 30.0 0.0
df.set_index(['Month', 'Dayname'], inplace=True)
</code></pre>
<p><a href="https://i.stack.imgur.com/dZb3u.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/dZb3u.png" alt="enter image description here"/></a></p>
<h3>数据框平均值:</h3>
<pre class="lang-py prettyprint-override"><code>Month Dayname ID AAA_BMITH AAA_4.1 AAA_CH
Jan Thu 7686.500000 0.0 28.045455 0.0
Jan Fri 7636.272727 0.0 28.136364 0.0
Jan Sat 7637.272727 0.0 27.045455 0.0
Jan Sun 7670.090909 0.0 27.090909 0.0
Jan Mon 7702.909091 0.0 27.727273 0.0
Jan Tue 7734.260870 0.0 27.956522 0.0
df_mean.set_index(['Month', 'Dayname'], inplace=True)
</code></pre>
<p><a href="https://i.stack.imgur.com/OGHCH.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/OGHCH.png" alt="enter image description here"/></a></p>
<h3>更新<code>df</code>:</h3>
<ul>
<li>此操作基于匹配的索引值</li>
<li>它不能同时处理多个列名,您必须获取感兴趣的列并遍历它们</li>
<li>注意,<code>AAA_1E</code>不在<code>df_mean</code></li>
</ul>
<pre class="lang-py prettyprint-override"><code>for col in df.columns:
if col in df_mean.columns:
df[col].fillna(df_mean[col], inplace=True)
</code></pre>
<p><a href="https://i.stack.imgur.com/oh8z9.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/oh8z9.png" alt="enter image description here"/></a></p>