<p>在复制了数据帧之后,我只想知道细节。。你知道吗</p>
<p>同时导入numpy以将<code>Nan</code>值设置为所需索引。。你知道吗</p>
<pre><code>import pandas as pd
import numpy as np
</code></pre>
<p>您的数据帧:</p>
<pre><code>$ df
A
0 Reviewer: Newbie | 35-44 on Treatment for 1
1 Reviewer: 45-54 on Treatment for less than 1
2 Reviewer: Ocetech| 65-74 Male on Treatment
3 Reviewer: virleo| 55-64 Female on Treatment
4 Reviewer: Diane perrin| 65-74 on Treatment for
</code></pre>
<p>您的索引列表:</p>
<pre><code>$ l1
[1, 3, 4]
</code></pre>
<p>基于列<code>A</code>的<code>loc</code>,使用Numpy将索引设置为<code>Nan</code>。。你知道吗</p>
<pre><code>df.loc[l1,'A'] = np.nan
</code></pre>
<p>结果:</p>
<pre><code>print(df)
A
0 Reviewer: Newbie | 35-44 on Treatment for 1
1 NaN
2 Reviewer: Ocetech| 65-74 Male on Treatment
3 NaN
4 NaN
</code></pre>
<p>如果您没有要替换到<code>NaN</code>的索引的长列表,您可以直接指定它们,而不是传递一个列表索引。你知道吗</p>
<pre><code>$ df.loc[[1,3,4],'A'] = np.nan
$ print(df)
A
0 Reviewer: Newbie | 35-44 on Treatment for 1
1 NaN
2 Reviewer: Ocetech| 65-74 Male on Treatment
3 NaN
4 NaN
</code></pre>
<h2>另一种方法:</h2>
<pre><code>$ df.rename(index={1:np.nan, 3:np.nan, 4:np.nan}, inplace=True)
</code></pre>