<p dir="auto">Hi there!</p>
<p dir="auto">I was trying to tweak the fliers (outliers) of a letter-value plot I am generating with seaborn (e.g. using properties of matplotlib for the traditional boxplot -- for instance: <a href="https://matplotlib.org/2.0.2/examples/statistics/boxplot_demo.html" rel="nofollow">https://matplotlib.org/2.0.2/examples/statistics/boxplot_demo.html</a>), but without success.</p>
<p dir="auto">I have a huge plot with several boxenplots side-by-side and I wanted to change the face color of my outliers so they match the body of the boxenplot. Since they are pretty tucked together, sometimes it's hard to differentiate which outliers belong to which distribution.</p>
<p dir="auto">Please, let me know if there is an obvious solution for this that I am not catching.</p>
<p dir="auto">Thanks so much!</p>
<p dir="auto">I want to draw a barplot facetted for different cateogories in a data frame.</p>
<p dir="auto">Each sub0barplot shows has as a y-axis another categorical variable. I expect the the y-axes to be shared across facets. If a specific y-category doesn't exist for a specific facet I expect seaborn to either throw an error or properly draw the bars only for those y-cateogories that are present and not draw any bars for those categories that are not present.</p>
<p dir="auto">However, what actually happens is seaborn just fills the bars from index 0 to whatever the maxum length of unique y-categories exists in a specific facet. Hence this producses false and wrong plots, as bars appear in the wrong places.</p>
<p dir="auto">Please consider either throwing an error or not drawing a bar when a y-category is not present for all facets.</p>
<p dir="auto">Example</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="iris = sns.load_dataset('iris')
iris['flowerID'] = np.tile(np.arange(0,50), 3)

tmp = iris.loc[iris.flowerID&lt;10].iloc[4:]
tmp['flowerID'] = [str(i) for i in tmp['flowerID']]
g = sns.FacetGrid(tmp, col=&quot;species&quot;, height=8)
g.map_dataframe(sns.barplot, y='flowerID', x='sepal_length')"><pre class="notranslate"><code class="notranslate">iris = sns.load_dataset('iris')
iris['flowerID'] = np.tile(np.arange(0,50), 3)

tmp = iris.loc[iris.flowerID&lt;10].iloc[4:]
tmp['flowerID'] = [str(i) for i in tmp['flowerID']]
g = sns.FacetGrid(tmp, col="species", height=8)
g.map_dataframe(sns.barplot, y='flowerID', x='sepal_length')
</code></pre></div>
<p dir="auto">Result is the following plot:<br>
<a target="_blank" rel="noopener noreferrer" href="https://user-images.githubusercontent.com/18192128/247990777-00268b06-e6d9-489e-b5f5-6bcd397e5b51.png"><img src="https://user-images.githubusercontent.com/18192128/247990777-00268b06-e6d9-489e-b5f5-6bcd397e5b51.png" alt="image" style="max-width: 100%;"></a></p>
<p dir="auto">However for setosa flowers bars should only appear at the IDs 4-9. The seabor bar chart makes you belief the sepal lengths are assigned to IDs 1-5.<br>
<a target="_blank" rel="noopener noreferrer" href="https://user-images.githubusercontent.com/18192128/247990901-6fdf9fd6-c375-4720-94f6-d41bb439f057.png"><img width="491" alt="image" src="https://user-images.githubusercontent.com/18192128/247990901-6fdf9fd6-c375-4720-94f6-d41bb439f057.png" style="max-width: 100%;"></a></p>