<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="sns.distplot(np.concatenate([np.zeros(100), np.ones(10)]))"><pre class="notranslate"><span class="pl-s1">sns</span>.<span class="pl-en">distplot</span>(<span class="pl-s1">np</span>.<span class="pl-en">concatenate</span>([<span class="pl-s1">np</span>.<span class="pl-en">zeros</span>(<span class="pl-c1">100</span>), <span class="pl-s1">np</span>.<span class="pl-en">ones</span>(<span class="pl-c1">10</span>)]))</pre></div>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
&lt;ipython-input-24-9543570a22a7&gt; in &lt;module&gt;()
----&gt; 1 sns.distplot(np.concatenate([np.zeros(100), np.ones(10)]))

/home/wiecki/miniconda3/lib/python3.4/site-packages/seaborn/distributions.py in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax)
    210         hist_color = hist_kws.pop(&quot;color&quot;, color)
    211         ax.hist(a, bins, orientation=orientation,
--&gt; 212                 color=hist_color, **hist_kws)
    213         if hist_color != color:
    214             hist_kws[&quot;color&quot;] = hist_color

/home/wiecki/miniconda3/lib/python3.4/site-packages/matplotlib/axes/_axes.py in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
   5676             # this will automatically overwrite bins,
   5677             # so that each histogram uses the same bins
-&gt; 5678             m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
   5679             m = m.astype(float)  # causes problems later if it's an int
   5680             if mlast is None:

/home/wiecki/miniconda3/lib/python3.4/site-packages/numpy/lib/function_base.py in histogram(a, bins, range, normed, weights, density)
    247                 n.imag += np.bincount(indices, weights=tmp_w.imag, minlength=bins)
    248             else:
--&gt; 249                 n += np.bincount(indices, weights=tmp_w, minlength=bins).astype(ntype)
    250 
    251         # We now compute the bin edges since these are returned

ValueError: operands could not be broadcast together with shapes (10,) (11,) (10,) 

&gt; /home/wiecki/miniconda3/lib/python3.4/site-packages/numpy/lib/function_base.py(249)histogram()
    248             else:
--&gt; 249                 n += np.bincount(indices, weights=tmp_w, minlength=bins).astype(ntype)
    250 "><pre class="notranslate"><code class="notranslate">---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
&lt;ipython-input-24-9543570a22a7&gt; in &lt;module&gt;()
----&gt; 1 sns.distplot(np.concatenate([np.zeros(100), np.ones(10)]))

/home/wiecki/miniconda3/lib/python3.4/site-packages/seaborn/distributions.py in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax)
    210         hist_color = hist_kws.pop("color", color)
    211         ax.hist(a, bins, orientation=orientation,
--&gt; 212                 color=hist_color, **hist_kws)
    213         if hist_color != color:
    214             hist_kws["color"] = hist_color

/home/wiecki/miniconda3/lib/python3.4/site-packages/matplotlib/axes/_axes.py in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
   5676             # this will automatically overwrite bins,
   5677             # so that each histogram uses the same bins
-&gt; 5678             m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
   5679             m = m.astype(float)  # causes problems later if it's an int
   5680             if mlast is None:

/home/wiecki/miniconda3/lib/python3.4/site-packages/numpy/lib/function_base.py in histogram(a, bins, range, normed, weights, density)
    247                 n.imag += np.bincount(indices, weights=tmp_w.imag, minlength=bins)
    248             else:
--&gt; 249                 n += np.bincount(indices, weights=tmp_w, minlength=bins).astype(ntype)
    250 
    251         # We now compute the bin edges since these are returned

ValueError: operands could not be broadcast together with shapes (10,) (11,) (10,) 

&gt; /home/wiecki/miniconda3/lib/python3.4/site-packages/numpy/lib/function_base.py(249)histogram()
    248             else:
--&gt; 249                 n += np.bincount(indices, weights=tmp_w, minlength=bins).astype(ntype)
    250 
</code></pre></div>
<p dir="auto">lmplot Method does not give a good sense of regressed line when axes boundaries are far from zero and not in scale. It might be a good idea to write a method or argument to somehow (either on the plot or as print) output the intercept and slope of the regressed line.</p>