--- /tmp/pyresample-1.22.3-2b85wqtrs/debian/python-pyresample-doc_1.22.3-2_all.deb
+++ python-pyresample-doc_1.22.3-2_all.deb
├── file list
│ @@ -1,3 +1,3 @@
│  -rw-r--r--   0        0        0        4 2021-12-10 07:48:41.000000 debian-binary
│  -rw-r--r--   0        0        0     2708 2021-12-10 07:48:41.000000 control.tar.xz
│ --rw-r--r--   0        0        0  3700952 2021-12-10 07:48:41.000000 data.tar.xz
│ +-rw-r--r--   0        0        0  3700936 2021-12-10 07:48:41.000000 data.tar.xz
├── control.tar.xz
│ ├── control.tar
│ │ ├── ./md5sums
│ │ │ ├── ./md5sums
│ │ │ │┄ Files differ
├── data.tar.xz
│ ├── data.tar
│ │ ├── ./usr/share/doc/python-pyresample-doc/html/api/pyresample.bucket.html
│ │ │ @@ -162,15 +162,15 @@
│ │ │  
│ │ │  <dl class="py method">
│ │ │  <dt class="sig sig-object py" id="pyresample.bucket.BucketResampler.get_max">
│ │ │  <span class="sig-name descname"><span class="pre">get_max</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skipna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyresample.bucket.BucketResampler.get_max" title="Permalink to this definition">¶</a></dt>
│ │ │  <dd><p>Calculate maximums for each bin with drop-in-a-bucket resampling.</p>
│ │ │  <div class="admonition warning">
│ │ │  <p class="admonition-title">Warning</p>
│ │ │ -<p>The slow <a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="(in pandas v1.3.4)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">pandas.DataFrame.groupby()</span></code></a> method is temporarily used here,
│ │ │ +<p>The slow <a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="(in pandas v1.3.5)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">pandas.DataFrame.groupby()</span></code></a> method is temporarily used here,
│ │ │  as the <a class="reference external" href="https://github.com/dcherian/dask_groupby">dask_groupby</a> is still under development.</p>
│ │ │  </div>
│ │ │  <dl class="field-list simple">
│ │ │  <dt class="field-odd">Parameters</dt>
│ │ │  <dd class="field-odd"><ul class="simple">
│ │ │  <li><p><strong>data</strong> (<em>Numpy</em><em> or </em><em>Dask array</em>) – Data to be binned.</p></li>
│ │ │  <li><p><strong>skipna</strong> (<em>boolean</em><em> (</em><em>optional</em><em>)</em>) – If True, skips NaN values for the maximum calculation
│ │ │ @@ -192,15 +192,15 @@
│ │ │  
│ │ │  <dl class="py method">
│ │ │  <dt class="sig sig-object py" id="pyresample.bucket.BucketResampler.get_min">
│ │ │  <span class="sig-name descname"><span class="pre">get_min</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_value</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">nan</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skipna</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyresample.bucket.BucketResampler.get_min" title="Permalink to this definition">¶</a></dt>
│ │ │  <dd><p>Calculate minimums for each bin with drop-in-a-bucket resampling.</p>
│ │ │  <div class="admonition warning">
│ │ │  <p class="admonition-title">Warning</p>
│ │ │ -<p>The slow <a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="(in pandas v1.3.4)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">pandas.DataFrame.groupby()</span></code></a> method is temporarily used here,
│ │ │ +<p>The slow <a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="(in pandas v1.3.5)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">pandas.DataFrame.groupby()</span></code></a> method is temporarily used here,
│ │ │  as the <a class="reference external" href="https://github.com/dcherian/dask_groupby">dask_groupby</a> is still under development.</p>
│ │ │  </div>
│ │ │  <dl class="field-list simple">
│ │ │  <dt class="field-odd">Parameters</dt>
│ │ │  <dd class="field-odd"><ul class="simple">
│ │ │  <li><p><strong>data</strong> (<em>Numpy</em><em> or </em><em>Dask array</em>) – Data to be binned.</p></li>
│ │ │  <li><p><strong>skipna</strong> (<em>boolean</em><em> (</em><em>optional</em><em>)</em>) – If True, skips NaN values for the minimum calculation