Overview: This project provides a comprehensive analysis of vehicle sales data, focusing on data preprocessing, feature engineering, market trends, and seller performance. Utilizing various data science techniques, the project uncovers key insights into car pricing dynamics, market segmentation, and seller strategies, offering valuable information for stakeholders in the automotive industry.

Key Features: Data Cleaning and Preprocessing: Detailed steps to handle missing values, outliers, and data inconsistencies. Feature Engineering: Creation of new features like car age and mileage per year to enhance predictive models. Market Analysis: Examination of car prices across different makes and models, and the impact of vehicle condition on pricing. Seller Performance Evaluation: Analysis of sales volume and average selling prices among different sellers. Clustering and Segmentation: Identification of distinct vehicle market segments using K-means clustering. Time Series Analysis: Exploration of temporal patterns in car sales data to identify trends and seasonality. Predictive Modeling: Use of machine learning techniques to predict car prices based on various features.

Contents: Data: The dataset used for this analysis, sourced from Kaggle's Vehicle Sales and Market Trends Dataset. Scripts: Python scripts used for data cleaning, analysis, visualization, and modeling. Results: Findings from the analysis, including visualizations and statistical summaries.

Usage: This repository is intended for educational and informational purposes. You are welcome to view the data and analysis results. Please note that the use, modification, or redistribution of this work is not permitted.

License: No license is applied to this repository. All rights are reserved, and the content is provided for viewing only. If you have any questions or need permissions, please contact the author.

Author: Tsz Fong Chan

Acknowledgments: Special thanks to Syed Anwar Afridi for providing the dataset used in this analysis.

For any inquiries or further information, please feel free to reach out.