Comparison notebook: Why flexibility matters?

[cetagostini]

Add a new Jupyter notebook to docs demonstrating a comparison between Interrupted Time Series (ITS) approaches and Synthetic Control methods. The notebook loads CausalPy's built-in sc dataset, sets up plotting and RNG seed, and walks through applying CausalImpact and CausalPy to the same data (treated unit 'actual', controls a–g, treatment at time 73) to highlight when synthetic control is the more appropriate method.

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PR Summary

Low Risk
Docs-only change that adds a toctree entry; no runtime or library behavior is affected.

Overview
Adds a new documentation example notebook, its_causalpy_vs_causalimpact.ipynb, to the Comparative Interrupted Time Series section by linking it in docs/source/notebooks/index.md.

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[read-the-docs-community]

Documentation build overview

📚 causalpy | 🛠️ Build #31356419 | 📁 Comparing a1d4a88 against latest (278e947)

🔍 Preview build

Show files changed (3 files in total): 📝 2 modified | ➕ 1 added | ➖ 0 deleted

File	Status
404.html	📝 modified
notebooks/index.html	📝 modified
notebooks/its_causalpy_vs_causalimpact.html	➕ added

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 94.35%. Comparing base (278e947) to head (a1d4a88).

Additional details and impacted files

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  Coverage   94.35%   94.35%           
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  Files          44       44           
  Lines        7517     7517           
  Branches      456      456           
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  Hits         7093     7093           
  Misses        262      262           
  Partials      162      162           

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