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title="Dendrogram"

seoDescription="A collection of dendrogram examples made with Python, coming with explanation and reproducible code"

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title="Dendrogram"

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<h2 id="What is it?">&#8505; &#65039; Two types of dendrogram</h2>

<p>

It is important to understand that dendrograms are used in 2 very

different conditions that are based on 2 different data inputs:

</p>

<ul>

<li>

<u>Hierarchical dataset</u>: think about a CEO managing team leads

managing employees and so on.

</li>

<li>

<u>Clustering result</u>: clustering divides a set of individuals

in group according to their similarity. Its result can be

visualized as a tree, often going together with a heatmap.

</li>

</ul>

<a href="https://www.data-to-viz.com/graph/dendrogram.html">

<Button size="sm">Read more about dendrogram</Button>

</a>

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</div>

<Spacing />

<Container>

<h2 id="Clustering & Matplotlib">

<Matplotlib />

Dendrogram for clustering with <code>Matplotlib</code>

</h2>

<p>

The <Link to="/400-basic-dendrogram">first chart</Link> of this

section explains how to build a basic dendrogram with Python and

<code>matplotlib</code>. It starts from a numeric matrix, compute the

similarity between each pair of item thanks to the{' '}

<code>linkage()</code> function and plot the result with the{' '}

<code>dendrogram()</code> function.

</p>

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<ChartImageContainer

imgName="400_Basic_Dendrogram"

caption="Most basic dendrogram and clustering with Python and Matplotlib"

linkTo="/401-customised-dendrogram"

/>

</Row>

<p>

The next post explains how to customize the output: change node and

edge features like color and shapes, select a specific part of the

tree and more.

</p>

<Row>

<ChartImageContainer

imgName="401_custom_Dendrogram2"

caption="Most basic dendrogram and clustering with Python and Matplotlib"

linkTo="/400-basic-dendrogram"

/>

<ChartImageContainer

imgName="401_custom_Dendrogram6"

caption="Horizontal dendrogram"

linkTo="/401-customised-dendrogram"

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<ChartImageContainer

imgName="401_custom_Dendrogram5"

caption="Cut the dendrogram at a specific height"

linkTo="/401-customised-dendrogram"

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<h2 id="Clustering & Seaborn">

<Seaborn />

Dendrogram, clustering and heatmaps with <code>Seaborn</code>

</h2>

<p>

It is very common to display the results of a clustering using a{' '}

<Link to="/heatmap">heatmap</Link>

with dendrograms around it. Fortunately the <code>Seaborn</code>{' '}

library makes it a breeze.

</p>

<p>

The examples below will guide you through the most usual needs. Note

however that data normalization should be your main focus here, as it

can massively impact the final visual result. (See{' '}

<Link to="/404-dendrogram-with-heat-map">this post</Link> for that).

</p>

<Link to="/heatmap">

<Button size="sm">Related: heatmap section</Button>

</Link>

<div style={{ maxWidth: '600px', margin: '0 auto', padding: 30 }}>

<Link to="/405-dendrogram-with-heatmap-and-coloured-leaves">

<ChartImage

imgName={'405_Dendro_and_heatmap_and_rowcolor'}

caption={

'A seaborn heatmap with clusterization and dendrogram applied'

}

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</Link>

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<Row>

<ChartImageContainer

imgName="404_Dendro_and_heatmap3"

caption="Most basic heatmap with dendrogram with seaborn"

linkTo="/404-dendrogram-with-heat-map"

/>

<ChartImageContainer

imgName="404_Dendro_and_heatmap9"

caption="Change color palette"

linkTo="/404-dendrogram-with-heat-map"

/>

<ChartImageContainer

imgName="404_Dendro_and_heatmap11"

caption="Learn how to normalize data in the heatmap, avoiding that kind of result"

linkTo="/404-dendrogram-with-heat-map"

/>

</Row>

</Container>

<Spacing />

<Container>

<h2 id="Hierarchichal">Dendrogram for hierarchical datasets</h2>

<p>

Dendrogram can also be used to display a hierarchy. A hierarchy as a

root node that gets divided in several children and so on.

</p>

<p>TODO</p>

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