Prompt

Get expert data visualization recommendations with code generation for multiple libraries and frameworks.

<visualization_request>
**Dataset Description:**
{DESCRIBE YOUR DATA: TYPE, SIZE, KEY VARIABLES}

**Analysis Goals:**
{WHAT INSIGHTS ARE YOU TRYING TO COMMUNICATE?}

**Audience:**
{WHO WILL VIEW THESE VISUALIZATIONS?}

<visualization_analysis>
Based on your data and goals, I'll provide:

1. **Visualization Type Recommendations:**
   <chart_selection>
   - Primary visualization: {Best chart type with rationale}
   - Supporting visualizations: {Complementary charts}
   - Interactive elements needed
   - Dashboard layout suggestions
   </chart_selection>

2. **Implementation Options:**
   <code_generation language="python">
   # Matplotlib/Seaborn implementation
   {Complete code with styling}
   </code_generation>
   
   <code_generation language="javascript">
   // D3.js implementation
   {Interactive web-based visualization}
   </code_generation>
   
   <code_generation language="r">
   # ggplot2 implementation  
   {Publication-ready graphics}
   </code_generation>

3. **Design Best Practices:**
   <design_guidelines>
   - Color palette selection
   - Accessibility considerations
   - Label and annotation strategies
   - Responsive design approach
   - Print vs. digital optimization
   </design_guidelines>

4. **Statistical Considerations:**
   <statistical_integrity>
   - Appropriate scale selection
   - Uncertainty visualization
   - Outlier handling
   - Aggregation methods
   - Misleading visualization avoidance
   </statistical_integrity>

5. **Storytelling Elements:**
   <narrative_flow>
   - Key message hierarchy
   - Visual flow direction
   - Annotation strategies
   - Title and subtitle crafting
   - Call-to-action placement
   </narrative_flow>
</visualization_analysis>

Please provide the most effective solution for my specific use case.
</visualization_request>