# ericmjl/Network-Analysis-Made-Simple

An introduction to network analysis and applied graph theory using Python and NetworkX

Repository: https://github.com/ericmjl/Network-Analysis-Made-Simple
Canonical: https://ross.abutalabs.com/products/network-analysis-made-simple
Homepage: https://ericmjl.github.io/Network-Analysis-Made-Simple/index.html
Language: Python
License: MIT
License Family: permissive
Topics: graph, network-analysis, networkx, networkx-graph, networkx2, graph-theory, tutorial, live-tutorial, python
Last push: 2026-08-11T19:53:47+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 97, release rhythm 8, longevity 100
- inputs: {"age_days": 4268, "days_push": 22, "days_rel": 500, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1118, forks 395 (observed 2026-08-28T04:03:39.278626+00:00)

## What it is
A tutorial collection of notebooks teaching practical graph theory and network analysis using Python and NetworkX. It is presented as a live workshop at conferences and also available as a web book and LeanPub eBook.

## Use cases
- learn network analysis with networkx
- introduction to graph theory in python
- hands-on tutorial for applied network science
- learn hubs, paths, cliques and bipartite graphs
- workshop material for teaching networkx
- case studies in graph analysis

## When to choose
- you want a beginner-friendly, practical introduction to graph theory with NetworkX
- you prefer learning through executable notebooks and case studies
- you are preparing to teach or attend a network analysis workshop

## When to avoid
- you need production graph analytics infrastructure or a maintained library
- you want advanced or exhaustive coverage of graph algorithms
- you need a tool rather than learning material

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, developer-tools
- domain: tutorials, data-science, education
- platform: python, cross-platform
- tags: networkx, graph-theory, network-analysis, jupyter-notebooks, tutorial, applied-graph-theory

## Member repositories
- ericmjl/Network-Analysis-Made-Simple (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:39.278626+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:41:28.379204+00:00, confidence not recorded.
  - readme: https://github.com/ericmjl/Network-Analysis-Made-Simple (fetched 2026-08-28T04:03:39.278626+00:00, sha 6baa7cc70f58)
  - homepage: https://ericmjl.github.io/Network-Analysis-Made-Simple/index.html (fetched 2026-08-29T12:45:27.780876+00:00, sha 8b2109075e7a)
- Data as of 2026-08-30T08:39:29.467469+00:00.