Electric Vehicle Market Analysis Dashboard

Overview

This project analyzes U.S. electric vehicle registration data using a Tableau dashboard. The goal is to understand EV adoption trends, BEV vs. PHEV distribution, manufacturer dominance, model popularity, average electric range, CAFV eligibility, and state-level concentration.

This is a business intelligence and data visualization project, not a machine learning project.

Business Problem

Electric vehicle adoption is growing quickly, but market trends vary by vehicle type, manufacturer, model year, geography, and incentive eligibility. Analysts, policymakers, and business teams need a clear dashboard to monitor adoption patterns, identify leading manufacturers and models, and understand where EV adoption is concentrated.

This dashboard turns EV registration data into visual insights that support market analysis, policy discussion, infrastructure planning, and business reporting.

Dataset

• Dataset: Electric Vehicle Population Data
• Records: 150,413 vehicles
• Scope: U.S. electric vehicle registrations
• Vehicle Types: Battery Electric Vehicles (BEV), Plug-in Hybrid Electric Vehicles (PHEV)
• Key Fields: Model year, make, model, EV type, electric range, state, CAFV eligibility

Dashboard Preview

Key Metrics

• Total Vehicles: 150,413
• Average Electric Range: 67.83 miles
• Total BEV Vehicles: 116,745
• BEV Share: 77.6%
• Total PHEV Vehicles: 33,668
• PHEV Share: 22.4%
• CAFV Eligible Vehicles: 62,887
• CAFV Unknown: 69,697
• CAFV Not Eligible: 17,829

Key Insights

• EV adoption peaked in 2023: Registrations reached 37.1K in 2023, showing strong recent growth before the partial 2024 count.
• BEVs dominate the dataset: Battery Electric Vehicles account for 77.6% of registered EVs, compared with 22.4% for PHEVs.
• Tesla leads by manufacturer: Tesla represents 68.9K vehicles, or 54.06% of total vehicles by make.
• Tesla Model Y and Model 3 are the top models: Model Y accounts for 18.95% of vehicles, while Model 3 accounts for 18.42%.
• Washington dominates state-level registrations: Washington accounts for the overwhelming majority of vehicles in this dataset.
• CAFV eligibility is mixed: 41.81% of vehicles are CAFV eligible, 46.34% have unknown eligibility, and 11.85% are not eligible.

Dashboard Features

The Tableau dashboard includes:

• KPI cards for total vehicles, BEV count, PHEV count, and average electric range
• Model-year trend line showing EV adoption over time
• State-level map for geographic distribution
• Top vehicle makes by total registrations
• CAFV eligibility donut chart
• Vehicle model table with make, EV type, total vehicles, and share of total
• Interactive filters for CAFV eligibility, EV type, model year, and state

Tools Used

Tableau, Data Cleaning, Data Visualization, Dashboard Design, Business Intelligence, Market Analysis

Repository Structure

Electric_Vehicle_Data_Analysis/
├── Dashboard.png
├── Electric_Vehicle_Population_Data.csv
├── ev.jpg
└── README.md

How to Use

1. Open Dashboard.png to review the final Tableau dashboard.
2. Use Electric_Vehicle_Population_Data.csv to inspect the underlying EV registration data.
3. Review the README insights to understand major EV adoption trends, manufacturer distribution, model popularity, and CAFV eligibility patterns.
4. Use the dashboard filters to explore EV adoption by CAFV eligibility, EV type, model year, and state.

Business Impact

This dashboard provides a quick market-level view of EV adoption and vehicle distribution. It helps users identify adoption trends, leading manufacturers, high-volume models, state-level concentration, and incentive eligibility patterns without manually reviewing the raw dataset.

Limitations

• The dashboard is based on the available EV population dataset and may not represent all U.S. EV registrations equally.
• Washington dominates the dataset, so geographic conclusions should be interpreted carefully.
• The 2024 count appears partial and should not be directly compared with full prior years.
• CAFV eligibility includes a large unknown category, limiting policy interpretation.
• This project is descriptive analytics only; it does not forecast EV adoption.

Future Improvements

• Add the Tableau workbook file if shareable
• Add calculated field documentation
• Add state-normalized metrics such as EVs per capita
• Add year-over-year growth calculations
• Add EV adoption forecasting by model year
• Add manufacturer-level trend analysis over time
• Add charging infrastructure or policy data for deeper geographic analysis