<p dir="auto">You can have a large frame in memory and want to drop a small percentage of labels with NA data just to clean things up. If you use drop() or dropna(), you will get a new object and effectively double the memory footprint. Favoring immutability is great, but under memory constraints this can be a killer.</p>
<p dir="auto">see related discussion in <a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="8580418" data-permission-text="Title is private" data-url="https://github.com/pandas-dev/pandas/issues/2325" data-hovercard-type="issue" data-hovercard-url="/pandas-dev/pandas/issues/2325/hovercard" href="https://github.com/pandas-dev/pandas/issues/2325">#2325</a></p>
<p dir="auto">Possible and/or desirable to add an inplace keyword to dropna? Maybe an out keyword, so you can avoid typing the assignment? [<strong>Edit:</strong> I guess out doesn't really make sense like it does for numpy ufuncs.] Don't really mind if there's a copy even I just get tired of always doing assignment to the same name when I'm doing pre-, post-processing, etc.</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="dataframe = dataframe.action()"><pre class="notranslate"><code class="notranslate">dataframe = dataframe.action()
</code></pre></div>