How to Retrieve Leaf Coordinates of a Scipy Dendrogram

What will you learn?

Discover how to extract leaf coordinates from a scipy dendrogram object with ease.

Introduction to the Problem and Solution

In this tutorial, we delve into the task of extracting leaf coordinates from a scipy dendrogram. Utilizing the powerful functions offered by the scipy library in Python, we will navigate through the process systematically. By following these steps, you will be able to successfully retrieve leaf coordinates and manipulate them according to your needs.


# Import necessary libraries
from scipy.cluster.hierarchy import dendrogram

# Assuming 'dendro' is your existing dendrogram object
leaf_coordinates = dendrogram_object['icoord']

# Utilize or display these leaf_coordinates as required

# Copyright PHD

Ensure to replace dendro with the actual variable name holding your dendrogram.


To fetch leaf coordinates from a scipy dendrogram, you must have an existing dendrogram object. The function dendrogram_object[‘icoord’] provides a list of x-coordinates for each node in the tree structure. These x-coordinates represent positions on the plot where leaves are situated.

By capturing and storing these x-coordinate values in leaf_coordinates, you gain the ability to effectively work with them for visualization or any other purposes within your Python script.

    How can I install SciPy library in Python?

    You can easily install SciPy using pip: pip install scipy

    Can I customize the appearance of my dendrogram plot?

    Yes, you have the flexibility to adjust various parameters such as colors, line styles, labels, etc., to enhance the visual representation of your dendrogram.

    Is it possible to convert these coordinates into another format?

    Absolutely! You can transform these coordinates based on your requirements using mathematical operations or specific conversion techniques.

    Are there any alternatives for extracting leaf coordinates apart from ‘icoord’ attribute?

    Certainly! There are additional attributes like ‘ivl’ (the labels) that offer different information about nodes/leaves in a dendogram which could be valuable based on your specific needs.

    How do I interpret these coordinate values?

    The coordinate values signify relative positions of leaves/nodes along the x-axis; understanding their relationship aids in effectively analyzing hierarchical clustering results.


    In conclusion, retrieving leaf coordinates from a Scipy Dendrogram involves accessing specific attributes provided by Scipy’s hierarchy module. By efficiently leveraging these functionalities through customized code implementations tailored towards individual project requirements, one can derive valuable insights essential for hierarchical clustering analysis applications.

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