# Skill 002

> Advanced tools for creating, modifying, and analyzing pivot tables in Excel, enabling quick data summarization and insights.

- Skill: `legendtkl/skill-002` (Agent Skill)
- Install (CLI): `npx skillmds@latest add legendtkl/skill-002`
- Raw SKILL.md: https://api.skillmd.com/api/skills/legendtkl/skill-002/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- License: Proprietary. LICENSE.txt has complete terms
- Author: legendtkl (https://skillmd.com/u/legendtkl)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/legendtkl/skill-002

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# Requirements for Outputs

## General Pivot Table Standards

### Data Source Integrity
- Ensure that the data source for pivot tables is complete and well-structured to avoid errors.
- Pivot tables should not reference cells that contain errors or are blank.

### Naming Conventions
- Use clear and descriptive names for pivot tables and their associated fields to enhance usability.

## Pivot Table Creation Techniques

### Basic Creation Steps
- Pivot tables should be created directly from well-structured data ranges.
- Example code snippet:
```python
import pandas as pd

def create_pivot_table(df):
    pivot_table = df.pivot_table(values='Sales', index='Product', columns='Region', aggfunc='sum')
    return pivot_table
```

### Advanced Modifications
- Users should be able to modify pivot tables to include calculated fields and filters as needed.
- Example code snippet:
```python
def add_calculated_field(pivot_table):
    pivot_table['Profit'] = pivot_table['Sales'] - pivot_table['Cost']
    return pivot_table
```

## Documentation and Validation Requirements

### Metadata Inclusion
- Each pivot table must include metadata specifying its source data and any calculations performed.
- Example: "Pivot Table based on Sales Data from 2023 Q1."

### Change Tracking
- Maintain a log of changes made to pivot tables to facilitate auditing and validation.