| name | python-viz |
| description | Python plotting and statistical-modelling libraries (matplotlib, seaborn, statsmodels) for the analyst presentation and statistical-methodology layers. Use when producing publication-quality figures or fitting statistical models in Python. Library-specific HOW for the tech-agnostic principles in the aops-tools analyst skill. |
Python Visualisation & Statistical Modelling (academicOps)
These libraries are one swappable implementation. The analyst skill owns the
statistical-methodology and presentation principles, which are library-neutral.
When to use
- You need to render a figure from PRE-COMPUTED data (presentation layer).
- You need to fit or diagnose a statistical model in Python (statistical-methodology
layer) — pair this with the analyst skill's
statistical-analysis reference for the
methodology that drives the choice of test/model.
Where the API detail comes from
Fetch current library documentation at the point of use. matplotlib, seaborn, and
statsmodels all move, and a copy pinned in this repo would be one more thing to keep
true. Which test, which model, and how to report it is the analyst skill's question,
not a library one.
