🚗 Factors Driving EV Adoption & Charging Station Deployment

📌 Overview

Electric Vehicle (EV) adoption is rapidly increasing, but the availability of charging infrastructure remains a key challenge. This project analyzes the factors influencing EV adoption and charging station deployment using Python-based data analytics.

📚 *This project was completed for academic use as part of MSA 8010: Data Programming under Professor Ugur Kursuncu at Georgia State University for the Master of Science in Analytics (MSA) program.

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🎯 Objective

• Examine key drivers of EV adoption trends.
• Analyze the availability and distribution of charging stations.
• Identify correlations between EV growth and socioeconomic factors.

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📊 Dataset

This analysis is based on multiple datasets, including:

• EV Sales Data – Yearly sales categorized by model and region.
• Charging Station Data – Locations, types, and station capacity.
• Demographics & Economic Data – Income levels, urbanization, and policies.

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🔍 Methodology

1. Data Collection & Cleaning

   • Standardized data formats and handled missing values.

2. Exploratory Data Analysis (EDA)

   • Analyzed EV sales trends and charging station growth.
   • Identified correlations using statistical methods.

3. Data Visualization

   • Used Matplotlib & Seaborn for visual storytelling.
   • Created heatmaps, line charts, and scatter plots for insights.

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📈 Key Findings

• EV Adoption Trends

  • EV sales increase in high-income, urban areas with incentives.
  • Charging availability positively impacts EV growth.

• Charging Station Deployment

  • Fast chargers are concentrated in high-demand regions.
  • Rural areas lag behind in infrastructure expansion.

• Economic & Policy Impact

  • Subsidies & tax rebates accelerate EV adoption.
  • Lower electricity costs drive consumer preference for EVs.

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🛠 Tech Stack

• Python: Data processing & analysis
• Pandas: Data manipulation
• Matplotlib & Seaborn: Data visualization
• Scikit-learn: Statistical analysis

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🎯 Contributors

👩‍💻 Lilly Parham
👩‍💻 Gracie Rehberg
👩‍💻 Pamela Alvarado-Zarate

📚 Georgia State University - Master of Science in Analytics

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📌 Note:

This project is for academic purposes and is based on public data regarding electric vehicle registrations, demographics, and charging station infrastructure.