data-analysis

Automate data analysis pipelines from EDA to publication-ready output.

127|22|Updated Feb 20, 2026

Search Tags:#research #data analysis #estimation #EDA #publication output

Ready to run

npx skills add https://github.com/flonat/flonat-research --skill data-analysis-flonat

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/flonat/flonat-research/tree/main/skills/data-analysis
Command: npx skills add https://github.com/flonat/flonat-research --skill data-analysis-flonat

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires R, Python, Stata, Julia, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the entire data analysis pipeline, from exploratory data analysis (EDA) to model estimation and publication-ready output, saving researchers significant time and ensuring accuracy.

Core Features & Use Cases

End-to-End Analysis: Automates EDA, estimation, and publication output tasks.
Multi-Language Support: Supports R, Python, Stata, and Julia for model estimation.
Use Case: Imagine you are analyzing a dataset for a research paper. Use this Skill to perform EDA, estimate models, and generate publication-quality tables and figures.

Quick Start

Use the data-analysis skill to run a full analysis on your dataset located at '/path/to/your/data'.

Frequently Asked Questions about data-analysis

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

FAQPage Schema

How do I automate exploratory data analysis and model estimation for a research dataset?▼

Automating exploratory data analysis and model estimation requires a pipeline that handles data exploration, statistical modeling, and output generation. This Skill automates that end-to-end workflow, from EDA to publication-ready output.

Does this data analysis pipeline support estimation in both R and Python?▼

Yes, the data analysis pipeline supports model estimation in both R and Python. It also includes compatibility with Stata and Julia, allowing researchers to use their preferred language for statistical modeling.

What is the best way to generate publication-ready output from statistical models?▼

Generating publication-ready output from statistical models is best handled by automating the pipeline from estimation to formatting. This Skill produces publication-quality tables and figures directly from your estimated models.

Can I use Stata or Julia for model estimation in an automated research pipeline?▼

Yes, you can use Stata or Julia for model estimation in an automated research pipeline. The Skill explicitly supports these languages alongside R and Python to execute estimation tasks and generate outputs.

Do I need to know R or Python to use this automated estimation pipeline?▼

Yes, you need knowledge of R, Python, Stata, or Julia to use this automated estimation pipeline. The Skill requires prerequisite understanding of these languages to properly configure and execute model estimations.