<div dir="ltr"><pre style="padding:0px;margin-top:0px;margin-bottom:0px;color:rgb(0,0,0);font-size:14px"><code>pandas!=0.17.0,>=0.16.0</code></pre><pre style="padding:0px;margin-top:0px;margin-bottom:0px;color:rgb(0,0,0);font-size:14px"><code><br></code></pre><pre style="padding:0px;margin-top:0px;margin-bottom:0px;color:rgb(0,0,0);font-size:14px"><code>should do what you need, I think</code></pre></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Mar 9, 2016 at 3:40 PM, Tennessee Leeuwenburg <span dir="ltr"><<a href="mailto:tleeuwenburg@gmail.com" target="_blank">tleeuwenburg@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">I'm not aware of a way to avoid 'cursed versions' of packages. For example, pandas 0.17.0 has an issue with duplicate rows. This bug is fixed in 0.17.1, but also the previous version was fine. I apologies if there is logic to handle this situation.<div><br></div><div>I would like to express this as a "latest version but not 0.17.0". This is because 'latest' might mean different things depending where you are getting your versions from (e.g. anaconda, pypi, OS packages).</div><div><br></div><div>I don't know what to suggest, but I thought this was an interesting use case and worth mentioning.<br clear="all"><div><br></div>
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