# GeostatsGuy/PythonNumericalDemos

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

Repository: https://github.com/GeostatsGuy/PythonNumericalDemos
Canonical: https://ross.abutalabs.com/products/pythonnumericaldemos
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: datanalytics, geostatistics, machine-learning, python
Last push: 2026-03-03T17:49:37+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 70, release rhythm 8, longevity 100
- inputs: {"age_days": 3246, "days_push": 183, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1473, forks 498 (observed 2026-08-28T04:04:49.584458+00:00)

## What it is
A collection of well-documented Jupyter Notebook demonstrations for spatial data analytics, geostatistics, and machine learning, created by Professor Michael Pyrcz to support university courses. It provides runnable example workflows with datasets so learners can repeat lecture examples hands-on.

## Use cases
- learn geostatistics with python notebooks
- spatial data analytics tutorials
- machine learning examples for students
- reproduce lecture workflows in python
- learn data analytics with well-documented notebooks
- interpolate spatial data with kriging in python

## When to choose
- you are a student or self-learner following Pyrcz's courses on geostatistics or data analytics
- you want runnable, well-commented notebook examples with accompanying datasets
- you need educational demonstrations of spatial and geostatistical methods in Python

## When to avoid
- you need a production-ready geostatistics library rather than teaching notebooks
- you want maintained, versioned software with an API instead of example workflows
- your use case is outside spatial data, geostatistics, or introductory ML

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, machine-learning, data-visualization, nlp
- domain: data-science, education, machine-learning, tutorials
- platform: python, cross-platform
- tags: geostatistics, spatial-data-analytics, jupyter-notebooks, educational, geostatspy

## Member repositories
- GeostatsGuy/PythonNumericalDemos (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:49.584458+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 2026-08-30T04:34:35.676598+00:00, confidence not recorded.
  - readme: https://github.com/GeostatsGuy/PythonNumericalDemos (fetched 2026-08-28T04:04:49.584458+00:00, sha 409b683ee95c)
- Data as of 2026-08-30T08:39:29.467469+00:00.