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A pipeline-oriented data transformation DSL for Python and Jupyter

Project description

Pivotal

Pivotal is a data analysis language for Python. It offers a concise syntax for common data operations that compiles to Pandas, Polars or DuckDB code. Pivotal's JupyterLab extension adds autocomplete, interactive viewer and GUI controls, making it a user friendly entry point to the Python data ecosystem.


A live-demo of Pivotal in Jupyter Lab is available via Binder:

JupyterLab demo

Features

Readable, Writable syntax — write data transformations in a simple declarative syntax

Multiple backends — compile to Pandas (default), Polars or in-process DuckDB (SQL)

JupyterLab integration%%pivotal cell magic, live object viewer, syntax highlighting, autocomplete, GUI controls, export to Python code

VS Code integration — syntax highlighting, autocomplete, interactive execution and code export

Plotting and tables — simple syntax for charts and publication-ready tables via matplotlib and Great Tables

Data packages — export all output (DataFrames, charts, tables) to a single Frictionless data package


Installation

pip install pivotal-lang

This installs the full feature set — Pandas, Polars, DuckDB, Great Tables.

For a minimal Pandas-only install:

pip install --no-deps pivotal-lang
pip install lark pandas matplotlib

JupyterLab extension

pip install pivotal-lab

VS Code extension

Install from the VS Code Marketplace, or build locally from editors/vscode.


Documentation

Full documentation including the complete syntax reference, backend guide, and API reference:

nealbob.github.io/pivotal-py


Contributing

Contributions are welcome! Please open an issue or pull request on GitHub.


License

MIT


Authors

Neal Hughes


Version History

  • v0.1.0 — Initial release

Contact & Support

For questions, issues, or feature requests please open an issue on GitHub or contact hughes.neal@gmail.com.

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