⚠️ samplics is no longer maintained. Use svy instead.svy is the successor to samplics, from the same author: the same survey methodology (design, sampling, weighting, estimation, small area models), rebuilt on Polars with a Rust core, an end-to-end workflow through reporting, and active development.
pip install svy
- Docs and migration guide: https://svylab.com/docs/svy
- Questions about migrating: https://github.com/samplics-org/svy/issues
samplics 0.6.x stays on PyPI and keeps working, but no bugs will be fixed and no new Python versions will be supported.
Samplics was a Python package for design-based analysis of complex survey data, covering sample size calculation, selection, weighting, estimation, and small area estimation. It has been superseded by svy.
If you use samplics in published research, please cite:
Diallo, M.S. (2021). samplics: a Python Package for Selecting, Weighting and Analyzing Data from Complex Sampling Designs. Journal of Open Source Software, 6(68), 3376. https://doi.org/10.21105/joss.03376
@article{Diallo2021,
author = {Diallo, Mamadou S.},
title = {samplics: a Python Package for Selecting, Weighting and Analyzing Data from Complex Sampling Designs},
journal = {Journal of Open Source Software},
year = {2021},
volume = {6},
number = {68},
pages = {3376},
doi = {10.21105/joss.03376},
url = {https://doi.org/10.21105/joss.03376}
}Created by svyLab · info@svylab.com