Data tools

Interactive data systems
Smaller data workflow tools built around validation, explicit data limits, and reproducible exports—not undocumented notebook logic. Streamlit supplies the interactive session in the browser; the repo still owns tests, config, and deploy behavior. Portfolio remains the primary route for larger data systems and API-heavy work; this page is secondary evidence.
  • Schema checks, row caps, and structured reject paths so bad inputs fail loudly instead of polluting downstream numbers.
  • Pytest-backed pipelines and pinned assumptions where they matter; exports match what ran on the server.
  • Reviewable outputs: HTML, CSV, JSON, Parquet, or PDF artifacts that can be saved and compared.

Portfolio centers on batch workflows, APIs, monitoring, and shared data definitions; this page shows the same habits in smaller interactive surfaces: tight validation, visible limits, and traceable outputs. Repos contain tests and deploy notes.

GitHub profile — opens everything public on my account. On this page, each project card links to that repo and its live demo in the footer.

Secondary tools in this track

Data cleaning toolkit
  • Streamlit
  • pandas
  • pytest
  • Parquet / JSON
  • Docker

Upstream prerequisite, not a side utility: downstream data workflows ingest the same reviewed tables. Multi-format inputs become auditable CSV/Parquet/JSON plus HTML step log and before/after views, capped near 100K rows; rules cover bad formats, duplicates, skewed categories, optional outliers, plus bundled samples for dry runs.

GitHubLive demo
EDA report generator
  • Streamlit
  • pandas
  • pytest
  • Jinja2
  • WeasyPrint

Read-only profiling dossier you can archive or forward: capped sampling with sheet picker, column summaries, correlations, histograms, and warnings, rendered to HTML from memory with optional PDF when WeasyPrint is available. Single-column junk files fail fast.

GitHubLive demo
Forecasting app
  • Streamlit
  • Holt-Winters
  • Plotly
  • Rolling backtest

Forecast workflow with honest baselines: resampled Holt-Winters by day/week/month only when seasonality is supportable; Plotly band with MAPE/MAE against naive; warnings and fallback reasons stay on-screen for reviewers.

GitHubLive demo

Each card links to source and a public instance. These tools support the main portfolio track but are not the primary data systems page.

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Data systems, APIs, batch workflows, and reproducible automation.