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Vehicle Market Analysis: Python and Jupyter-based project for exploring market trends, visualizing sales data, and deriving actionable insights.

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Vehicle Sales Trend Analysis in Great Britain (2001–2024)

Project Overview

This project analyzes automotive sales data from 2001 to 2024.
The main objective is to identify trends in car sales across body types, manufacturers, and fuel types, and to highlight how the market has evolved.

Dataset

  • Rows: 102,892
  • Columns: 102
  • Features:
    • BodyType, Make, GenModel, Model, Fuel
    • Quarterly sales data from 2001Q1 to 2025Q1

Tools & Libraries

  • Python (Pandas, NumPy)
  • Visualization: Matplotlib, Seaborn, Plotly
  • Jupyter Notebook

Key Steps

  1. Data cleaning & preprocessing
  2. Exploratory Data Analysis
  3. Visualization of sales patterns
  4. Insights & business conclusions

Results

  • Top manufacturers by total sales identified.
  • Shift in fuel type preference observed over time.
  • Clear growth/decline patterns in specific car body types.

Vehicle Registrations per Year

Trends Over Time

Cars Brands Popularity Visualization

Top 10 Car Brands Ranking by Year Top 10 Car Brands Ranking by Year

Top 10 Car Brands Over Years Top 10 Car Brands Over Years

Top 10 Car Brands Race Chart Top 10 Car Brands Race Chart

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Vehicle Market Analysis: Python and Jupyter-based project for exploring market trends, visualizing sales data, and deriving actionable insights.

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