In brevi
dawgdad is a Python library for data scientists, machine learning engineers, and statisticians. It contains statistical and graphical functions for making sense of data to create information and understanding.
- Supervised machine learning
- Six Sigma methodology
- Regular expressions
- Process capability
- Process variation
- Excel file edits
- Taguchi Methods
- Data Science
- Automation
- Analytics
Why dawgdad?
- Equivalent Python functions that are available in R, SAS, JMP, Minitab
- Other packages have limited process control analysis features
- Other packages are abandoned or inadequately supported
- Functions to support measurement system analysis
- Functions to simplify statistics, graphs, etc.
- Functions to support process control charts
- Functions to support SQL functionality
- Develop a free open source package
Documentation
Full documentation is available at https://dawgdad.readthedocs.io/en/latest/.
Installation
This project is publish on https://pypi.org/project/dawgdad/.
pip install dawgdad
References
To cite this repository, please use:
@software{dawgdad, author = {Gilles Pilon}, title = {dawgdad}, url = {https://github.com/gillespilon/dawgdad}, version = {1.0.11}, date = {2026-10-24} }
Metadata
Release files for dawgdad 1.0.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| dawgdad-1.0.11.tar.gz | 83.6 kB | Without provenance | Details for dawgdad-1.0.11.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| dawgdad-1.0.11-py3-none-any.whl | Python 3 | none | any | Details for dawgdad-1.0.11-py3-none-any.whl |
Total release size: 171.9 kB
Release files / dawgdad-1.0.11.tar.gz
| Download URL | dawgdad-1.0.11.tar.gz |
|---|---|
| Size | 83.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
24878ca08f6b9b876327ac5dba37031b3ee3c9f0c56b1c7da2d18d5eac6b401e
|
|
BLAKE2b-256 checksum How to use checksums |
55e6fc8b8f814555455579345fda602e75f36d5fb23229317960f55d1118d8db
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-requests/2.34.2
|
Release files / dawgdad-1.0.11-py3-none-any.whl
| Download URL | dawgdad-1.0.11-py3-none-any.whl |
|---|---|
| Size | 88.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f91944570ae58b8e393d0f10b86e353cbaea094b65e78c1a83a55edc2ea654f7
|
|
BLAKE2b-256 checksum How to use checksums |
e8e3a26d9935bb2f343462a51927fb132abdcdd3c851951b5bf81b3ce149572e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-requests/2.34.2
|
Security for dawgdad 1.0.11
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.