design-research-analysis#

The analysis layer for reproducible design-research event data.

What This Library Does#

design-research-analysis supports sequence analysis, language analysis, embedding maps, and statistical modeling over unified event-table inputs. It is built for recurring research workflows where validation, provenance, and repeatability are first-order concerns.

Unified-table validation and column derivation are core features, not pre-processing footnotes. They make downstream analyses composable, reproducible, and easier to compare across studies.

CI Coverage Examples Passing Public API In Examples Docs

Highlights#

  • Unified-table coercion, validation, and mapper-driven derived columns

  • Dataset profiling, schema checks, and codebook generation

  • Sequence analysis for Markov chains and Hidden Markov Models

  • Language analysis for semantic convergence, topic discovery, and sentiment

  • Embedding maps and clustering for embedding-space inspection

  • Statistical workflows for comparisons, regression, mixed effects, and power

  • Runtime provenance capture for reproducible study artifacts

Typical Workflow#

  1. Start from a unified event table or an exported design-research-experiments events.csv artifact.

  2. Validate and, when needed, derive missing analysis columns.

  3. Run sequence, language, embedding-map, and/or statistical workflows.

  4. Persist JSON summaries, CSV exports, and provenance manifests.

  5. Rejoin findings to runs.csv and evaluations.csv for study context.

Note

Start with Quickstart for the shortest runnable path, or Experiments-To-Analysis Handoff if you already have events.csv from design-research-experiments.

Guides#

Learn the table model, setup flow, and repeatable analysis patterns that shape a stable downstream research pipeline.

Examples#

Browse runnable examples covering the major analysis surfaces.

Reference#

Look up the stable import surface, CLI behavior, and dependency guidance for repeatable analysis environments.

Integration With The Ecosystem#

The Design Research Collective maintains a modular ecosystem of libraries for studying human and AI design behavior.

  • design-research-agents implements AI participants, workflows, and tool-using reasoning patterns.

  • design-research-problems provides benchmark design tasks, prompts, grammars, and evaluators.

  • design-research-analysis analyzes the traces, event tables, and outcomes generated during studies.

  • design-research-experiments sits above the stack as the study-design and orchestration layer, defining hypotheses, factors, conditions, replications, and artifact flows across agents, problems, and analysis.

Together these libraries support end-to-end design research pipelines, from study design through execution and interpretation.

Ecosystem diagram showing experiments above agents, problems, and analysis.

Start Here#