Agent skill
great-tables
Publication-quality tables in Python with rich styling, formatting, conditional formatting, and export to HTML/images - inspired by R's gt package
Install this agent skill to your Project
npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/data/analysis/great-tables
SKILL.md
Great Tables
When to Use This Skill
USE Great Tables when:
- Publication tables - Creating tables for reports, papers, or presentations
- Data presentation - Professional display of analysis results
- Conditional formatting - Highlighting patterns with colors and icons
- Complex layouts - Multi-level headers, grouped rows, footnotes
- HTML reports - Interactive tables for web-based reports
- Quick formatting - Need polished tables without manual styling
- Dashboard components - Tables in Streamlit/Dash applications
- Export requirements - Need PNG or PDF output
DON'T USE Great Tables when:
- Large datasets - Over 1000 rows for display (use pagination)
- Interactive editing - Need editable cells (use Streamlit data_editor)
- Real-time updates - Streaming data display
- Complex interactivity - Sorting, filtering (use DataTables or AG Grid)
- Raw data exploration - Use pandas display or ydata-profiling
Prerequisites
# Basic installation
pip install great_tables
# With all optional dependencies
pip install great_tables pandas polars
# For image export (PNG/PDF)
pip install great_tables webshot
# Using uv (recommended)
uv pip install great_tables pandas polars
# Verify installation
python -c "from great_tables import GT; print('Great Tables ready!')"
Complete Examples
Example 1: Financial Report Table
from great_tables import GT, html
from great_tables import style, loc
import pandas as pd
import numpy as np
def create_financial_report(
data: pd.DataFrame,
title: str = "Financial Report",
output_path: str = "financial_report.html"
*See sub-skills for full details.*
### Example 2: Sales Dashboard Table
```python
from great_tables import GT, html
from great_tables import style, loc
import pandas as pd
import numpy as np
def create_sales_dashboard_table(output_path: str = "sales_dashboard.html") -> GT:
"""
Create sales dashboard table with KPIs and sparklines.
"""
*See sub-skills for full details.*
### Example 3: Scientific Data Table
```python
from great_tables import GT
from great_tables import style, loc
import pandas as pd
import numpy as np
def create_scientific_table(output_path: str = "scientific_table.html") -> GT:
"""
Create publication-quality scientific data table.
"""
*See sub-skills for full details.*
## Version History
- **1.0.0** (2026-01-17): Initial release
- Basic table creation and styling
- Column formatting (currency, percent, date)
- Conditional formatting and color scales
- Row and column grouping
- Footnotes and annotations
- Export to HTML and images
- Complete report examples
- Integration with Streamlit and Polars
- Best practices and troubleshooting
## Resources
- **Official Documentation**: https://posit-dev.github.io/great-tables/
- **GitHub**: https://github.com/posit-dev/great-tables
- **PyPI**: https://pypi.org/project/great-tables/
- **Gallery**: https://posit-dev.github.io/great-tables/examples/
---
**Create publication-quality tables with Great Tables - beautiful data presentation made easy!**
## Sub-Skills
- [1. Basic Table Creation](1-basic-table-creation/SKILL.md)
- [2. Column Formatting](2-column-formatting/SKILL.md)
- [3. Styling and Colors](3-styling-and-colors/SKILL.md)
- [4. Conditional Formatting](4-conditional-formatting/SKILL.md)
- [5. Grouped Rows and Columns](5-grouped-rows-and-columns/SKILL.md)
- [6. Footnotes and Annotations (+1)](6-footnotes-and-annotations/SKILL.md)
- [Great Tables with Streamlit (+1)](great-tables-with-streamlit/SKILL.md)
- [1. Keep Tables Focused (+3)](1-keep-tables-focused/SKILL.md)
- [Common Issues](common-issues/SKILL.md)
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