Ministats
ministats is lightweight Python for learning statistics
that includes helper functions for data analysis,
probability visualizations,
and statistical analysis procedures.
The goal is to show code implementations of the standard stats procedures used in STATS 101 courses
that are easy to understand for Python beginners.
- Docs: ministats.readthedocs.io
- Features:
- Code implementations from scratch that closely match the math calculations.
- Leverages probability distributions defined in
scipy.stats. - Includes both classical analytical approximation methods like t-tests and modern methods like simulations, bootstrap estimation, and permutation tests.
- Free software: MIT license
Installation
To install the ministats library,
run the following command in a terminal:
$ python -m pip install ministats
To use ministats inside a Jupyter notebook or Colab notebook,
run the following %-magic command in a code cell:
%pip install ministats
Quickstart
INSERT NOTEBOOK quickstart.ipynb AS MARKDOWN SOURCE
Textbook
The ministats library was developed as the support code
for the No Bullshit Guide to Statistics,
which is an intro-to-stats textbook
that uses a computational approach to teaching probability and statistics concepts.
The book explains concepts using words, math formulas, visualizations, and code examples.
The ministats library contains implementations of all the statistical procedures
discussed in the book
written as concise, easy-to-read Python code.
To learn more about the book, consult the links below:
- Table of contents for Part 1 and Part 2
- Book preview PDFs:
- Concept maps from the books:
statistics_concepts.pdf - Python tutorial: bit.ly/pytut3
- Book website: noBSstats.com
- Announcement blog post
- Buy PDF here: gum.co/noBSstats
- Print version coming soon (January 2027).
Computational notebooks
To see examples of the ministats library in action,
you can check out the computational notebooks that accompany the book.
- View notebooks online: noBSstats.com/notebooks/
- Play with the notebooks in the cloud: https://mybinder.org/v2/gh/minireference/noBSstats/main
- Run the notebooks locally by following the instructions here.
- Watch this playlist with video tutorials that accompany the book.
Roadmap
Here are some tasks I need to take care of before the v1.0 release, which will be the version that accompanies the first edition of the No Bullshit Guide to Statistics:
- add text
- finish adding
docs/ - move
plots/figures.pyplotting functions toplots/book/figures.py - remove
plots/figuresplotting functions fromministatsnamespace - add more statistical tests:
- chi-square tests for categorical data
- one-sample equivalence test
- two-sample equivalence test
- add more tests
Testing
The statistical procedures implemented in the ministats library
are tested against the functions from scipy.stats and statsmodels
to make sure they give the same answers.
History
0.5.20 (2026-10)
- Latest version including lots of updates based on Reading Group feedback.
0.2.0 (2023-03-28)
- Imported plotting functions from
plot_helpers.py(in main namespace for now)
0.1.0 (2023-06-29)
- First release on PyPI.
1 maintainer
Metadata
1 maintainer
Release files for ministats 0.5.21
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