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data-analysis

Automate end-to-end R data analysis workflows from exploration to publication-ready outputs.

Updated Aug 27, 2026
Search Tags:#workflow#analysis#visualization#statistics#data-analysis#r#reproducible-research
One-click install
npx skills add https://github.com/diegosolarfuentes/geopolitics-gvc --skill data-analysis-diegosolarfuentes
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/diegosolarfuentes/geopolitics-gvc/tree/main/.claude/skills/data-analysis
Command: npx skills add https://github.com/diegosolarfuentes/geopolitics-gvc --skill data-analysis-diegosolarfuentes

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

End-to-end data analysis in R that automates exploration, modeling, and publication-ready outputs, reducing manual scripting and ensuring reproducible workflows.

Core Features & Use Cases

  • End-to-end workflow from data loading to regression and result publication
  • Reproducible analysis pipelines suitable for academic research and policy reports
  • Use Case: Given a dataset, run exploration, fit models (e.g., linear regression with robust standard errors), and generate formatted tables and figures for a manuscript

Quick Start

Run the complete R-based data-analysis workflow on your dataset to produce diagnostics, models, and publication-ready outputs.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I automate a reproducible data analysis workflow in R?▼

You can automate an end-to-end R data analysis workflow that covers setup, exploration, modeling, and publication-ready outputs, saving scripts to scripts/R and outputs to output/ directories for reproducible research.

What is the best way to generate publication-ready outputs from an R dataset?▼

Generating publication-ready outputs from an R dataset is best handled by an automated pipeline that produces formatted tables, figures with a unified project theme, and RDS files for objects to support academic research and policy reports.

Can I run linear regression with robust standard errors using an automated R pipeline?▼

Yes, you can run linear regression with robust standard errors using an automated R pipeline that fits models during the main analysis phase and generates formatted tables and figures for manuscripts.

Does this reproducible research workflow save R scripts and outputs to specific directories?▼

Yes, this reproducible research workflow saves R scripts to the scripts/R directory and saves generated outputs, figures, and RDS objects to the output/ directory to maintain a structured and reproducible project environment.

How do I create formatted tables and figures for a manuscript from R exploration data?▼

You can create formatted tables and figures for a manuscript by running an automated R pipeline that transitions from data exploration to publication-ready outputs, applying a consistent project theme to all visualizations.

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