Bellevue TDM White Paper - Interactive Data Visualization Tool

🎯 Overview

This interactive visualization tool provides comprehensive access to all 36 datasets from the City of Bellevue's Transportation Demand Management (TDM) White Paper (2025). The tool enables dynamic exploration, comparison, and analysis of commute mode share trends from 2010-2024.

📊 Datasets Included

American Community Survey (ACS) Data

1. Resident Data (C08301, 1-Year) - Charts 1-6

   • Mode share for people who live in Bellevue
   • Tracks: SOV, Transit, Work-from-Home, Overall Mode Share
   • Comparisons: Bellevue vs. King County vs. Washington State

2. Commuter Data (C08601, 1-Year) - Charts 7-12

   • Mode share for people who work in Bellevue
   • Same metrics as resident data
   • Regional comparisons included

3. Comprehensive Commuter Data (DP03) - Charts 13-18

   • Detailed breakdown of all commute modes
   • Combined data from multiple ACS tables

4. Five-Year Estimates (DP03, 5-Year) - Charts 19-25

   • Smoothed trends using rolling 5-year averages
   • Greater statistical reliability

Commute Trip Reduction (CTR) Program Data

5. Non-Drive Alone Rates - Charts 27-31

   • Historical trends from 1993-2022
   • Downtown vs. outside downtown comparisons
   • Site consistency analysis

6. Vehicle Miles Traveled (VMT) - Charts 32, 35-36

   • Average VMT per one-way commute trip
   • Total VMT trends
   • Weighted and unweighted comparisons

7. Program Methodology - Charts 33-34

   • Weighted vs. unweighted analysis
   • Impact of worksite size on metrics

🚀 Quick Start

Requirements

• Python 3.8 or higher
• pip (Python package manager)

Installation

1. Install Dependencies

pip install streamlit plotly pandas

2. Run the Application

streamlit run tdm_visualization_app.py

Or use the provided script:

./run_tdm_app.sh

3. Access the Dashboard The application will automatically open in your default web browser at:

http://localhost:8501

📱 Features

Navigation

• Category Selection: Browse datasets by source and type
• Chart Selection: Access any of the 36 individual charts
• Interactive Visualization: Hover for detailed data points

Display Options

• Toggle data tables on/off
• Show/hide statistical summaries
• Adjustable chart height (400-800px)
• Export capabilities

Data Context

Each chart includes:

• Data Source: ACS table number or CTR program
• Description: What the data represents
• Time Period: Years covered
• Important Notes: Methodology and interpretation guidance

Statistical Analysis

For each dataset series:

• Average: Mean value across time period
• Maximum: Peak value
• Minimum: Lowest value
• Change: First-to-last comparison with directional indicators

Export Options

• JSON: Complete dataset with all 36 charts
• CSV: Category-specific data tables
• Download buttons in sidebar

📈 Key Insights

COVID-19 Impact

• 2021: 48% of Bellevue workers worked from home (up from 1.3% in 2016)
• Dramatic shift in commute patterns
• Data interpretation requires pandemic context
• Dashboard includes COVID-19 timeline marker

Geographic Comparisons

All trend charts compare three levels:

1. Bellevue (city-specific data)
2. King County (regional context)
3. Washington State (statewide comparison)

Mode Categories

• Single-Occupancy Vehicle (SOV) / Drive Alone
• Transit (bus, light rail, commuter rail)
• Work from Home (emerged as major category post-2020)
• Carpool/Vanpool
• Walk/Bike
• Other modes

🎯 Use Cases

Policy Analysis

• Track progress toward TDM goals
• Evaluate program effectiveness
• Identify trends and patterns

Regional Comparison

• Benchmark Bellevue against King County
• Compare to state averages
• Assess relative performance

Historical Trends

• Long-term patterns (1993-2024 for CTR data)
• Pre/post-pandemic comparisons
• Mode shift analysis

Program Evaluation

• CTR worksite performance
• Downtown vs. non-downtown differences
• VMT reduction impacts

📚 Data Sources

American Community Survey (ACS)

• Agency: U.S. Census Bureau
• Frequency: Annual (1-year and 5-year estimates)
• Coverage: Geographic areas (Bellevue, King County, Washington)
• Key Tables:
  • C08301 (Residents)
  • C08601 (Commuters)
  • DP03 (Detailed Demographics)

Commute Trip Reduction (CTR) Program

• Agency: Washington State Department of Transportation
• Frequency: Biennial surveys
• Coverage: Major employers (>100 employees in urban areas)
• Metrics:
  • Non-drive alone rates
  • Vehicle miles traveled (VMT)
  • Mode share by worksite

🔍 Technical Details

File Structure

├── tdm_visualization_app.py    # Main Streamlit application
├── tdm_chart_data.json         # Extracted data from all 36 charts
├── run_tdm_app.sh             # Quick start script
└── README.md                   # This file

Data Format (JSON)

{
  "chart_N": {
    "number": N,
    "title": "Chart Title",
    "type": "scatter|bar|line",
    "series": [
      {
        "name": "Series Name",
        "x_values": [...],
        "y_values": [...]
      }
    ]
  }
}

Technologies Used

• Streamlit: Web application framework
• Plotly: Interactive charting library
• Pandas: Data manipulation and CSV export
• Python: Core programming language

🎨 Visualization Types

The dashboard automatically selects appropriate visualization types:

1. Time Series Line Charts

   • Used for: Trends over years (2010-2024)
   • Features: Multiple series comparison, COVID-19 marker
   • Interaction: Hover for exact values, unified hover mode

2. Bar Charts

   • Used for: Category comparisons
   • Features: Grouped bars for multi-series
   • Interaction: Click legend to hide/show series

3. Pie Charts

   • Used for: Mode share breakdowns (single year)
   • Features: Percentage labels, interactive segments
   • Interaction: Click to isolate segments

📋 Comprehensive Plan Integration

The dashboard references all 13 TDM goals from Bellevue's 2044 Comprehensive Plan (TR-4 through TR-16), providing context for how the data supports policy development and evaluation.

🔄 Data Updates

Updating the Dashboard

1. Extract updated .docx file with new charts
2. Run extraction script to update tdm_chart_data.json
3. Restart Streamlit application

Adding New Charts

The system is designed to automatically accommodate additional charts beyond the current 36.

⚠️ Important Notes

Data Interpretation

• Pre-COVID (2010-2019): Baseline trends
• 2020: Pandemic onset, incomplete data
• 2021-2022: Major shifts due to work-from-home
• 2023-2024: Emerging post-pandemic patterns

Statistical Significance

• 1-year ACS estimates: Less stable, more current
• 5-year ACS estimates: More stable, less current
• Consider sample sizes when interpreting changes

Methodology Differences

• ACS Data: Survey-based, represents all workers
• CTR Data: Program-based, large employers only
• Different populations and methodologies = different results

🤝 Support & Contact

For questions about:

• Data Sources: U.S. Census Bureau, WSDOT CTR Program
• Methodology: See White Paper documentation
• Technical Issues: Check Streamlit documentation

📄 License & Attribution

Document: City of Bellevue Transportation Demand Management White Paper, 2025 Data Sources:

• U.S. Census Bureau American Community Survey
• Washington State Commute Trip Reduction Program

🔮 Future Enhancements

Potential additions:

• Predictive trend modeling
• Goal tracking visualizations
• Scenario comparison tools
• Mobile-responsive design improvements
• PDF report generation
• API access for data queries

📞 Getting Help

Common Issues

Dashboard won't start

# Check Python version
python --version  # Should be 3.8+

# Reinstall dependencies
pip install --upgrade streamlit plotly pandas

Port already in use

# Use different port
streamlit run tdm_visualization_app.py --server.port 8502

Data not loading Ensure tdm_chart_data.json is in the same directory as the application.

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Created: December 2025
Version: 1.0
For: City of Bellevue Transportation Demand Management Program