Market size analysis using Python. The provided dataset contains the following columns, each representing different aspects of the electric vehicle (EV) population in the United States:
VIN (1-10): Partial Vehicle Identification Number. County: The county in which the vehicle is registered. City: The city in which the vehicle is registered. State: The state in which the vehicle is registered. It appears that this dataset may be focused on Washington (WA) state. Postal Code: The postal code where the vehicle is registered. Model Year: The year of the vehicle model. Make: The manufacturer of the vehicle. Model: The model of the vehicle. Electric Vehicle Type: The type of electric vehicle, e.g., Battery Electric Vehicle (BEV). Clean Alternative Fuel Vehicle (CAFV) Eligibility: Eligibility status for clean alternative fuel vehicle programs. Electric Range: The maximum range of the vehicle on a single charge (in miles). Base MSRP: The Manufacturer’s Suggested Retail Price. Legislative District: The legislative district where the vehicle is registered. DOL Vehicle ID: Department of Licensing Vehicle Identification. Vehicle Location: Geographic coordinates of the vehicle location. Electric Utility: The electric utility service provider for the vehicle’s location. 2020 Census Tract: The census tract for the vehicle’s location. The primary objective of this analysis is to leverage historical EV registration data to understand the current market penetration of EVs, predict future market growth, and identify key trends and factors driving market expansion. The specific goals include:
Assess the historical growth trend of EV registrations. Forecast future EV registrations based on historical trends. Analyze the distribution of EV registrations across different models, makes, and geographical regions. Estimate the market size and growth potential of the EV market for upcoming years. Provide insights to support stakeholders in decision-making processes related to production, infrastructure planning, and policy formulation.