svy Learn

Learning Resources for Complex Survey Data Analysis

Tutorials, technical notes, case studies, and workshops for the svy Python package — complex survey design, weighting, and analysis.

Author

Mamadou S. Diallo, Ph.D.

Modified

May 11, 2026

Tutorials, technical notes, and case studies for the svy Python package — complex survey design, weighting, and analysis. Start with the technical notes, explore case studies, or dive into the svy documentation.

Quick Links

📝 Technical Notes

Short-form articles covering specific topics, methods, and techniques.

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🔬 Case Studies

Real-world applications of svy on national survey microdata.

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🎓 Workshops

Structured, hands-on learning experiences for deeper skill building.

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📚 Books

Comprehensive guides covering survey methodology from start to finish.

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Latest Technical Notes

How Fast Is svy? Performance Benchmarks Against R’s survey

Performance

Survey Methods

Python

Timings for means, totals, ratios, proportions, domain estimates and replicate-weight variance in Python’s svy 0.22.1, compared with svy 0.18.2 and R’s survey 4.5, at 50,000 to 1,000,000 rows.

Aug 4, 2026

Python’s svy vs R’s survey: Identical Results Across 37 Estimators

Validation

Survey Methods

Python

svy reproduces R’s survey package to six decimals across 37 estimators — Taylor, BRR, jackknife, bootstrap, SDR, quantiles, singleton PSUs, correlation, covariance, cross-tabs, t-tests, contrasts, marginal effects, and survey GLMs.

Jan 10, 2026

svy: Design-Based Survey Analysis in Python

Survey Methods

Python

Data Science

svy is an open-source Python library for complex survey data design and analysis—bringing stratified, clustered, and weighted estimators to the modern data-science ecosystem.

Nov 1, 2025

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Recent Case Studies

svy on India’s Periodic Labour Force Survey, 2023-24

Labour force

India

Panel data

Variance estimation

Does a rotating panel change the procedure? India’s labour force survey revisits urban households for four quarters. For levels it changes the weight, not the estimator; for change between quarters it halves the standard error; and it moves the level itself.

Sep 27, 2026

Mamadou S. Diallo

India’s Time Use Survey 2024: from diary to estimate

Time use

India

Data wrangling

Turning a 10-million-row time diary into person-level estimates with standard errors, and reproducing every table in India’s Time Use Survey 2024 fact sheet.

Sep 11, 2026

Mamadou S. Diallo

svy on the Nigeria GHS-Panel, 2018/19 to 2023/24

Panel data

Nigeria

Living standards

Two waves of the LSMS-ISA General Household Survey-Panel reproduced in Python: the 2018/19 report under the Wave 4 weight, the 2023/24 report under the longitudinal weight, and the report’s change tables, with the standard errors a panel design earns.

Sep 6, 2026

Mamadou S. Diallo

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Featured Workshops

2025 Medical Expenditure Panel Survey, Household Component (MEPS-HC)

true

In this document, we use Python and the svy library to reproduce the 2025 MEPS Workshop (originally conducted in R, see GitHub Repository).

Oct 27, 2025

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About svy

svy is a Python package for the design, analysis, and reporting of complex survey data. It provides tools for:

Sample Design: stratified, cluster, and multi-stage sampling
Weighting: calibration, post-stratification, and weight adjustments
Estimation: point estimates, variances, and confidence intervals
Analysis: regression, cross-tabulation, and subgroup analysis

New to svy?

Check out the svy documentation for installation instructions and API reference.