data-analysis

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

1|Updated May 12, 2020
One-click install
npx skills add https://github.com/jakerbrown/jakerbrown.github.io --skill data-analysis-jakerbrown
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/jakerbrown/jakerbrown.github.io/tree/main/.claude/skills/data-analysis
Command: npx skills add https://github.com/jakerbrown/jakerbrown.github.io --skill data-analysis-jakerbrown

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Facilitates end-to-end data analysis workflows in R, enabling users to explore, model, and generate publication-ready outputs efficiently.

Core Features & Use Cases

  • Data Loading and Exploration: Load datasets, generate summaries, and visualize distributions to understand data structure.
  • Statistical Analysis: Perform regression analyses and diagnostic checks on panel or cross-sectional data.
  • Reporting: Create well-formatted tables and figures suitable for academic or professional publication.
  • Use Case: A researcher wants to analyze survey panel data, run fixed effects regressions, and prepare tables and figures for a journal article.

Quick Start

Run R scripts to load your dataset, explore its properties visually and statistically, conduct regression analysis, and produce ready-to-publish tables and figures.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I automate R data analysis from exploration to publication-ready reports?▼

Automate R data analysis by running scripts that load datasets, explore distributions, conduct regression modeling, and compile summaries into publication-ready tables and figures.

Can I run fixed effects regressions and generate diagnostic plots for panel data in R?▼

Yes, run fixed effects regressions and generate diagnostic plots for panel data using the fixest package, while visualizing distributions and conducting statistical checks across your dataset.

What R packages do I need for comprehensive regression analysis and reporting?▼

Comprehensive regression analysis and reporting require the fixest, modelsummary, and tidyverse R packages to automate modeling, generate diagnostic plots, and format publication-ready outputs.

How do I create publication-ready tables from regression summaries in R?▼

Create publication-ready tables from regression summaries in R by using the modelsummary package to format statistical outputs into well-structured figures and tables suitable for journals.

What is the best way to streamline a full-cycle data analysis workflow in R?▼

Streamline full-cycle data analysis in R by automating exploration, modeling, and reporting tasks end-to-end, efficiently processing datasets to generate diagnostic plots and compile regression summaries.