Improve example clarity with comprehensive docstrings and structured output

[Copilot]

Examples lacked proper documentation and clear structure, making them difficult to understand and learn from. Community detection examples needed verification.

Changes

Added comprehensive docstrings to 6 examples (571 lines added):

• example_powerlaw_computation.py - Power-law distribution analysis
• example_entanglement.py - Multilayer network entanglement metrics
• example_manipulation.py - Network operations (9 numbered sections)
• example_CBSSD.py - Semantic subgroup discovery workflow
• example_n2v_embedding.py - Node2Vec embedding generation
• example_visualization.py - Embedding-based layouts

Each example now includes:

• Module-level docstring with learning objectives and prerequisites
• Structured output with numbered sections and visual separators
• Key takeaways summary at end
• Installation guidance for missing dependencies

Before:

# compute and visualize powerlaw distributions (and other alternatives)
# SKIP_CI: external_deps

import networkx as nx
# ...code with no explanation...

After:

"""
Compute and Visualize Power-Law Distributions in Networks

Teaches:
- Fit and visualize power-law distributions on node degrees
- Compare power-law fitting on simple NetworkX graphs vs. multilayer networks
- Test for scale-free properties using built-in statistical tests

Prerequisites:
- mpmath library for power-law fitting: pip install mpmath
- Optional dataset: epigenetics.gpickle (from py3plex datasets)
"""

# Structured sections with clear headers
print("=" * 70)
print("[1] Analyzing power-law distribution on NetworkX graph...")
# ...well-documented code...

Verification

Community detection algorithms (Louvain, Leiden, DSL-based, Pipeline-based) all tested and working correctly.

Original prompt

---

This section details on the original issue you should resolve

<issue_title>Example clarity</issue_title>
<issue_description>Go over examples, make sure they are all clear/self explanatory. Make sure community detection algorithms work fine.</issue_description>

Comments on the Issue (you are @copilot in this section)

• Fixes Example clarity #1072

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