Time Series Visualization Best Practices

Optimize my time series visualization:

Data Characteristics:
- Time span: [start to end]
- Granularity: [minute/hour/day/week/month/year]
- Data points: [count]
- Series count: [single/multiple]
- Seasonality: [patterns if known]
- Missing data: [gaps present?]

Visualization Goals:
- Primary insight: [trend/pattern/anomaly/comparison]
- Time context: [historical/real-time/forecast]
- Comparison: [periods/series/benchmarks]
- Action: [what decision does this support?]

Current Issues (if any):
- [List problems with current visualization]

Design Decisions:

1. Chart Type Selection
   - Line vs area vs bar
   - Continuous vs discrete
   - Stacked vs overlaid

2. Time Axis Design
   - Tick frequency
   - Label format
   - Range selection
   - Zoom/pan capability

3. Multiple Series Handling
   - Same axis vs dual axis
   - Legend design
   - Hover interaction
   - Series toggling

4. Aggregation Strategy
   - Roll-up options
   - Drill-down capability
   - Summary statistics

5. Annotation Needs
   - Event markers
   - Reference lines (targets, averages)
   - Trend lines
   - Forecasts

6. Special Considerations
   - Gaps and missing data
   - Outlier handling
   - Confidence intervals
   - Seasonal adjustment

Tool: [D3.js/Matplotlib/Tableau/Power BI]

Provide optimized implementation with complete code.