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figure

Generate journal-ready econometrics figures in Python, R, and Stata.

Updated Apr 15, 2026
Search Tags:#visualization#r#matplotlib#stata#econometrics#ggplot2#figure-generation
One-click install
npx skills add https://github.com/sheehe/coase --skill figure
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: figure
Source: https://github.com/sheehe/coase/tree/main/%E5%AE%9E%E8%AF%81%E7%A7%91%E7%A0%94%E6%8F%92%E4%BB%B6/econometrics/econometrics/skills/figure
Command: npx skills add https://github.com/sheehe/coase --skill figure

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Econometrics researchers struggle to produce publication-quality figures that meet journal formatting standards, consuming valuable time on typography, sizing, and export settings.

Core Features & Use Cases

  • Journal-ready defaults for Python (matplotlib), R (ggplot2), and Stata graphs with consistent fonts, colors, and dimensions.
  • Coverage of common econometric figure types including event study plots, coefficient plots, binscatter, RDD visualizations, density plots, time-series, and multi-panel figures.
  • Export-ready outputs in PDF vector formats and grayscale-safe palettes, with notes on sample definitions, legends, and captioning for journal submission.

Quick Start

Tell me the figure type and data you want to visualize, and I will generate a publication-ready econometrics figure ready for journal submission.

Frequently Asked Questions about figure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create publication-quality econometrics figures for journal submission?▼

Publication-quality econometrics figures apply journal-ready defaults for fonts, line widths, dimensions, and color palettes. You can generate export-ready vector PDFs for event-study plots, coefficient plots, and binscatter by using enforced journal formatting standards.

Can I generate event-study plots and RDD visualizations in both R and Python?▼

Yes, you can generate event-study plots and RDD visualizations across Python, R, and Stata workflows. The templates provide cross-language code for consistent figure generation using matplotlib and ggplot2.

What is the best way to format matplotlib or ggplot2 figures for top economics journals?▼

The best way to format figures for top economics journals is to apply enforced journal standards for typography, sizing, and grayscale-safe color palettes. This ensures your matplotlib and ggplot2 outputs meet strict journal submission formatting requirements.

Do I need to manually configure vector export settings for econometric figures?▼

No, you do not need to manually configure vector export settings. The templates enforce journal standards for vector PDF export and grayscale-safe palettes automatically, reducing setup time for your econometric figures.

Does this solution support multi-panel time-series and density plots in Stata?▼

Yes, this solution supports multi-panel time-series and density plots in Stata. It provides ready-to-use code templates and best-practice notes for these common econometric figure types alongside Python and R workflows.

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