View Our Tutorials Online

Many coding tutorials are available in the Tutorials folder of our GitHub repository. For the quickest, zero-setup experience, open them in Google Colab using the "Open in Colab" links.

Colab runs entirely in your browser, so you don’t need to install Python or an IDE (Integrated Development Environment).

You can also view our tutorials on GitHub, but its preview sometimes fails for larger Jupyter notebooks; examples of these rendering issues are shown at the end of this page. To download any tutorial, open it on GitHub and choose the down-arrow icon (top-right menu) to save the file locally.

Recommended: Open in Colab

Click the "Open" link in the "Open in Colab" column of the following tables to immediately run, edit, and save a copy to your Google Drive.

Notebooks (Open in Colab)

Getting Started

Notebook	Description	Open in Colab	View on GitHub
Quickstart	Install, load data, and run your first analysis.	Open	Source
Local vs. Global Quintiles	Compare local vs global binning for value-to-state mapping.	Open	Source

Dissimilarity & Clustering

Notebook	Description	Open in Colab	View on GitHub
Dissimilarity Measures	Compute and compare sequence dissimilarity metrics.	Open	Source
Clustering: Hierarchical vs. PAM	Compare Ward's method and PAM on the same data, evaluate agreement and cluster quality.	Open	Source

Multi-Domain Sequence Analysis

Notebook	Description	Open in Colab	View on GitHub
Multidomain Sequence Analysis	End-to-end analysis across multiple domains per subject.	Open	Source
Polyadic Sequence Analysis	Analyze polyadic sequences (multi-actor interactions).	Open	Source
Multidomain Sequence Analysis: CombT	Python script (.py) for a CombT analysis workflow on multidomain sequences.	Open	Source
Polyadic Sequence Analysis: Script	Python script (.py) version of the polyadic analysis workflow.	Open	Source

Hidden Markov Models

Notebook	Description	Open in Colab	View on GitHub
HMM & Mixture HMM (mvad)	Identify hidden life stages and cluster trajectory types in school-to-work transitions.	Open	Source
HMM (pairfam)	Fit a hidden Markov model to family and activity trajectories from pairfam.	Open	Source
Multichannel HMM (biofam)	Model marriage, parenthood, and residence as parallel channels in a joint HMM.	Open	Source
Non-Homogeneous HMM (pairfam)	Incorporate covariates that affect transition probabilities with NHMM.	Open	Source

Why GitHub preview may fail

Sometimes GitHub fails to render a notebook (.ipynb) and shows:

Unable to render code block

You might see a screen like this:

This is a known limitation of GitHub’s preview for large outputs or complex notebooks.

To download the tutorial, click here:

Author: Yuqi Liang; Yapeng Wei