🔋 Electric Vehicle Data Analysis 📊

This project showcases data analysis and visualization on Electric Vehicle (EV) registrations across the United States using Python. It was completed as part of a task from Innomatics Research Labs.

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📁 Dataset Information

• Records: 112,634
• Features: VIN, Make, Model, Model Year, Electric Range, Base MSRP, State, Electric Utility, etc.
• Source: Provided CSV dataset (Electric Vehicle Registration)

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🧪 Tasks Completed

📌 Task 1: Exploratory Data Analysis (EDA)

🔹 Univariate Analysis

• Count of Electric Vehicle Types (BEV, PHEV)
• Top 5 EV Manufacturers
• Model Year Distribution

🔹 Bivariate Analysis

• Electric Range vs Base MSRP (Scatterplot)
• Electric Range by Make (Boxplot)

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📌 Task 2: Choropleth Visualization

Using plotly.express, interactive maps were created:

• EV Distribution by State
• Animated Choropleth: Year-wise EV growth from 2016 to 2023

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📌 Task 3: Racing Bar Chart

Using bar_chart_race, an animated bar chart video was generated:

• Top 10 EV Makes over the years (Model Year-wise growth)

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🔍 Key Insights

• ✅ BEVs are more common than PHEVs.
• 🚗 Top EV brands: Tesla, Chevrolet, Nissan, Ford
• 🗺️ States like California, Washington, Florida show the highest EV penetration.
• 📈 Steep increase in EV adoption post-2017.

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📦 Libraries Used

• pandas
• numpy
• seaborn
• matplotlib
• plotly.express