language-ranking-chart

name	language-ranking-chart
description	Create professional bar charts for programming language and software rankings with proper styling and TIOBE index formatting

Language Ranking Chart Skill

Overview

This skill creates visually appealing bar charts specifically for programming language rankings, software popularity metrics, and similar comparison data.

Workflow

1. Fetch Rankings - Search for current ranking data (TIOBE, Stack Overflow, GitHub)
2. Validate Data - Ensure rating percentages sum reasonably
3. Create Chart - Use matplotlib with ranking-specific styling
4. Apply Ranking Theme - Professional colors with ranking hierarchy emphasis
5. Save and Display - Export PNG with embedded summary table

Implementation

import matplotlib.pyplot as plt

def create_ranking_chart(data: dict, title: str, source: str, filename: str):
    """Create a ranking bar chart with professional styling."""
    plt.figure(figsize=(10, 6))
    
    colors = ['#2ecc71', '#3498db', '#9b59b6', '#f39c12', '#e74c3c'][:len(data)]
    bars = plt.bar(range(len(data)), list(data.values()), color=colors)
    
    plt.title(f'{title}\nSource: {source}', fontsize=14, fontweight='bold')
    plt.xticks(range(len(data)), list(data.keys()), rotation=45)
    plt.ylabel('Rating (%)')
    plt.xlabel('Programming Language')
    
    # Add value labels
    for bar, val in zip(bars, data.values()):
        plt.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.2, 
                f'{val}%', ha='center', va='bottom', fontsize=10)
    
    plt.tight_layout()
    plt.savefig(filename, dpi=150)
    plt.close()
    return filename

Best Practices

• Use TIOBE-style green-to-red color gradients for top rankings
• Include source attribution in title
• Add percentage labels on bars for precision
• Limit to top 5-10 items for readability
• Use tight_layout() to prevent label cutoff

Output Format

Returns PNG file plus summary table with rank, language, and rating columns.