---
id: great-tables
version: "0.23.0"
license: MIT License Copyright (c) 2022-2026 Posit Software, PBC Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the… (full text in the JSON record)
license_treatment: permissive
maintenance: active
---

# great-tables — Easily generate information-rich, publication-quality tables from Python.

License: permissive · Maintenance: active · Downloads: 683.2K/mo

## What it is and what it does

Great Tables is a Python library for creating formatted, visually polished tables from DataFrame data. It takes Pandas or Polars DataFrames as input and lets you compose tables with headers, footers, row labels (stubs), column spanners, and cell-level formatting—such as currency, dates, and numbers—before rendering to HTML or image output. The library emphasizes a composable, method-chaining API where you build tables incrementally by applying formatting and layout operations.

The package is designed for both everyday table display needs and publication-quality output. It comes with 16 built-in datasets for experimentation and is commonly used in notebook environments and Quarto documents. The active maintenance, low install friction, and permissive MIT license make it accessible for data analysis, reporting, and documentation workflows across scientific, financial, healthcare, and general software development contexts.

Use it for:

- Generate formatted financial or statistical reports from DataFrames with currency and number formatting applied.
- Create publication-ready tables for research papers, dashboards, or documentation with headers, footers, and styled columns.
- Build interactive HTML tables in Jupyter notebooks or Quarto documents with custom cell formatting and layout.
- Display date-based data with locale-aware formatting using Babel integration.
- Render large datasets as styled HTML or image tables for web or print distribution.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Great Tables transforms Pandas or Polars DataFrames into formatted, publication-quality HTML tables or images with headers, footers, column spanners, and cell-level formatting.

Yes. Great Tables is actively maintained, has low install friction, carries a permissive MIT license, and solves a clear problem—turning DataFrames into polished, formatted tables. It's well-suited for anyone doing data reporting, analysis, or documentation in Python. No known security vulnerabilities as of 2026-08-14.

## Install

pip install great-tables
uv add great-tables
poetry add great-tables

## Installing great-tables

Before you install: Low friction: pure Python wheel with 8 runtime dependencies (multimark, faicons, htmltools, importlib-metadata, nokap, typing_extensions, Babel, importlib-resources). Active maintenance with a release 18 days ago; last commit 2026-08-14.

License in practice: MIT License (permissive): you can use, modify, and distribute Great Tables freely in commercial and private projects with minimal restrictions, provided you retain the copyright notice and license text.

Quickstart:

pip install great_tables

from great_tables import GT
from great_tables.data import sp500

sp500_mini = sp500[(sp500["date"] >= "2010-06-07") & (sp500["date"] <= "2010-06-14")]
GT(sp500_mini).tab_header(title="S&P 500").fmt_currency(columns=["open", "high", "low", "close"])

Requires Python 3.10 or later.

Verify before relying:

- Whether image rendering requires additional system dependencies beyond the listed Python packages.
- Performance characteristics with large DataFrames (row/column count limits).
- Compatibility with Jupyter, Quarto, and other notebook environments beyond the documented examples.

## Package facts

- License: MIT License Copyright (c) 2022-2026 Posit Software, PBC Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 683.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python table formatting, dataframe to html table, pandas table rendering, polars table display, formatted table generation, table styling and layout, data table visualization, dataframe-rendering, table-formatting, html-generation

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