Table Generation

by lingzhi2279e6c085d65e3No license386 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 7 months ago

Generate publication-quality LaTeX tables from experimental results. Convert JSON/CSV data to booktabs-styled tables with bold best results, multi-row layouts, and proper captions. Use when creating result tables, comparison tables, or ablation tables for papers.

Includes scriptsDocuments & Office
AI-generated overview

Converts experimental results from JSON or CSV into publication-ready LaTeX tables with booktabs styling and bold best results.

What it does
This skill turns experimental result data into LaTeX table source for papers. It supports comparison, ablation, descriptive, multi-dataset, and custom table types, bolding best results, marking second-best with underlines, adding significance stars, and using multirow layouts for method categories. It produces booktabs-styled tables with captions, labels, and optional table notes.
When to use it
Use it when creating result tables, comparison tables, or ablation tables for a paper. It fits situations where experimental numbers already exist in JSON, CSV, or inline form and need to become LaTeX table code.
Requirements
Requires Python to run the bundled script scripts/results_to_table.py, plus a LaTeX environment with booktabs, multirow, multicol, and threeparttable packages for compiling the output. It ships an executable script and a reference file of table templates.

Table Generation

Convert experimental results into publication-ready LaTeX tables.

Input

  • $0 — Table type: comparison, ablation, descriptive, custom
  • $1 — Data source: JSON file, CSV file, or inline data

Scripts

Generate LaTeX table from JSON/CSV

bash
python ~/.claude/skills/table-generation/scripts/results_to_table.py \  --input results.json --type comparison \  --bold-best max --caption "Performance comparison" \  --label tab:main_results

Supports: comparison, ablation, descriptive, multi-dataset table types. Additional flags: --type multi-dataset for methods x datasets x metrics layout, --significance for p-value stars, --underline-second for second-best results.

References

  • LaTeX table templates and examples: ~/.claude/skills/table-generation/references/table-templates.md

Table Types

comparison — Main results table

  • Rows = methods (baselines + ours), Columns = metrics/datasets
  • Bold the best result in each column
  • Include mean +/- std when available
  • Use \multirow for method categories (Supervised, Self-supervised, etc.)

ablation — Ablation study table

  • Rows = variants (full model, minus component A, minus component B, ...)
  • Columns = metrics
  • Bold the full model result
  • Use checkmarks for component presence

descriptive — Dataset/statistics table

  • Dataset characteristics, hyperparameters, or summary statistics
  • Clean formatting with proper units

custom — Free-form table

  • User specifies layout and content

Required Packages

latex
\usepackage{booktabs}    % \toprule, \midrule, \bottomrule\usepackage{multirow}    % \multirow\usepackage{multicol}    % multi-column layouts\usepackage{threeparttable}  % table notes

Output Format

Always generate tables with:

  1. booktabs rules (\toprule, \midrule, \bottomrule)
  2. \caption{} and \label{tab:...}
  3. Bold best results using \textbf{}
  4. Table notes via threeparttable when needed
  5. Proper alignment (l for text, c or r for numbers)

Rules

  • Only include numbers from actual experimental logs — never hallucinate results
  • All numbers must match the data source exactly
  • Use $\pm$ for standard deviations
  • Use \underline{} for second-best results when appropriate
  • Keep tables compact — avoid unnecessary columns
  • Use table* for wide tables spanning two columns
  • Add glossary/notes for abbreviated column headers

Related Skills

  • Upstream: data-analysis, experiment-code
  • Downstream: paper-writing-section, paper-compilation
  • See also: figure-generation

Source and attribution

Source:lingzhi227/agent-research-skillsinskills/table-generationat commit9e6c085

License: No license

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