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HyunjunJeon
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data-analysis

Execute pandas code in LocalShellBackend to analyze tabular datasets.

Updated Aug 27, 2026
Search Tags:#pandas#statistics#data-analysis#multi-turn#data-processing#local-shell
One-click install
npx skills add https://github.com/HyunjunJeon/SDS-AX-Advanced-2026-1 --skill data-analysis-hyunjunjeon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/HyunjunJeon/SDS-AX-Advanced-2026-1/tree/main/Day-03/advanced_study/skills/data-analysis
Command: npx skills add https://github.com/HyunjunJeon/SDS-AX-Advanced-2026-1 --skill data-analysis-hyunjunjeon

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates data analysis tasks by executing pandas code in a LocalShellBackend and supports multi-turn analysis to derive insights.

Core Features & Use Cases

  • Plan analysis using a structured workflow and write_todos
  • Explore: inspect data shape, dtypes, missing values
  • Analyze: execute pandas code to compute statistics, aggregations, and visuals
  • Iterate: refine results through follow-up questions and extended analysis
  • Deliver: present results in a clear, markdown-friendly format

Quick Start

Provide your dataset and ask the AI to outline the plan with write_todos and then run pandas analysis to produce a structured report.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I automate pandas data analysis on CSV files through multi-turn conversations?▼

Automated pandas data analysis on CSV files is executed in a LocalShellBackend using a structured multi-turn workflow that plans steps, explores data, runs aggregations, and delivers markdown-formatted insights.

Can I run iterative exploratory data analysis on Excel datasets with pandas?▼

Iterative exploratory data analysis on Excel datasets is supported by executing pandas code in a local shell, allowing you to inspect dtypes, compute statistics, and refine results through follow-up questions.

Do I need Python 3.12 and LocalShellBackend to run pandas code for data analysis?▼

Executing pandas code for data analysis requires a Python 3.12+ LocalShellBackend environment with pandas installed to enforce the plan, explore, analyze, iterate, and deliver workflow.

What is the best way to structure a multi-turn data processing workflow?▼

The best way to structure multi-turn data processing is using a plan, explore, analyze, iterate, and deliver workflow, where initial steps are outlined with write_todos before running pandas computations.

Does this data analysis approach work with statistics and aggregations on tabular datasets?▼

Data analysis with statistics and aggregations works with tabular datasets like CSV and Excel by executing pandas code locally to compute descriptive statistics and derive structured insights.

How does the plan and write_todos workflow handle missing values during data analysis?▼

The plan and write_todos workflow handles missing values during data analysis by systematically exploring data dtypes and missing values first, then iterating with pandas code to clean and compute statistics.

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