golden-jupyter-topics

Imported from yusufkaraaslan/skill_seekers (tests/golden/phase2/jupyter_topics/SKILL.md). Install upstream with npx skills add yusufkaraaslan/skill_seekers --skill jupyter_topics. Copyright stays with the author.

Golden_Jupyter_Topics Notebook Skill

Use when testing the golden_jupyter_topics golden build

📋 Notebook Information

Kernel: Python 3

Language: python 3.11.4

💡 When to Use This Skill

Use this skill when you need to:

• Understand golden_jupyter_topics concepts and analysis workflow
• Reference code examples and their outputs
• Reproduce data analysis or computation steps
• Review methodology, visualizations, and results
• Find library usage patterns and best practices

📖 Section Overview

Total Sections: 5

Content Breakdown:

• Data Loading: 1 sections
• Evaluation: 1 sections
• Setup: 1 sections
• Other: 2 sections

🔑 Key Concepts

Main topics covered in this notebook

Major Topics:

• Getting Started

Subtopics:

• Modeling Results

📦 Dependencies

3 package(s) imported

• numpy
• pandas
• sklearn

⚡ Quick Reference

Common documentation patterns found:

Getting Started (1 sections):

• Getting Started (section 1)

Modeling (1 sections):

• Modeling Results (section 5)

📝 Code Examples

High-quality code cells from notebook

Bash Examples (1)

Example 1 (Quality: 5.0/10):

pip install pandas

Python Examples (3)

Example 1 (Quality: 9.5/10):

def long_example():
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    x3
...

In [2] (Quality: 7.5/10):

import pandas as pd
df = pd.read_csv('data.csv')
df.head()

Example 3 (Quality: 2.0/10):

%timeit broken()

📊 Notebook Statistics

• Total Sections: 5
• Code Cells: 2
• Markdown Cells: 2
• Raw Cells: 1
• Notebooks: 1
• Programming Languages: 2

Language Breakdown:

• python: 3 code cells
• bash: 1 code cells

🗺️ Navigation

Reference Files:

• references/section_s2-s2.md - Data Loading
• references/section_s5-s5.md - Evaluation
• references/section_s1-s1.md - Setup
• references/section_s3-s4.md - Other

See references/index.md for complete notebook structure.

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