packages = ["bokeh", "pandas", "numpy", "networkx", "diagrams", "scikit-learn", "pillow", "matplotlib", "plotly"] [[fetch]] files = ["diagrams_base.py"] from = "../../python/diagrams/" [[fetch]] files = ["pyscript_manager.py", "data.py"] to_folder = "lib" from = "../../python/lib/" [[fetch]] files = ["bokeh_utils.py"] from = "../../python/bokeh/" [[fetch]] files = ["matplotlib_utils.py", "plotly_utils.py"] from = "../../python/matplotlib/" [[fetch]] files = ["agent.py", "trainer.py", "utils.py", "metrics_chart.py", "crossover.py", "__init__.py"] to_folder = "ml/neuro" from = "../../python/ml/neuro/" [[fetch]] files = ["trainer.py"] to_folder = "ml/grokking" from = "../../python/ml/grokking/"

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These interactive network graphs visualize relationships...

🕸️ Full StackOverflow Network

Shows all 115 programming languages...

Full network using Kamada-Kawai layout:

🔗 Clique Analysis

A "clique" is a group of nodes...

Clique detection using the SAME cached data:

⭐ Eigenvector Centrality

Measures each node's influence...

Eigenvector centrality analysis:

💻 Programming Languages Network

Focuses specifically on major programming languages...

Programming language subgraph:

Bokeh + NetworkX

🕸️ What is NetworkX?

NetworkX is Python's most popular library...

📊 The Dataset

This network contains 115 nodes...

  • Name (e.g., "python", "javascript", "django")
  • Group/category (color coding)
  • Node size (popularity/activity)
  • Edges connecting it to related technologies

🔍 Network Analysis Concepts

Each visualization demonstrates key graph analysis techniques:

  • Degree: Number of connections...
  • Cliques: Groups where every node...
  • Centrality: How important/influential...
  • Subgraphs: Extracting portions...
  • Layouts: Algorithms that position...

🎨 Layout Algorithms

Different layouts reveal different aspects...

  • Kamada-Kawai: Optimizes distances...
  • Spring (Fruchterman-Reingold): Force-directed...

💡 How to Read These Graphs

  • Nodes (circles): Technologies/languages...
  • Edges (lines): Show relationships...
  • Colors: Different groups/categories...
  • Size: In full/clique/language...
  • Tools: Pan to move around...

View source files
Adapted from this Kaggle

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🐍 Python Console