Car Sales Analysis

Abstract

1. Introduction

Factors Affecting Car sales Volume between 2019 and 2020 Link: https://github.com/danawoodruff/carsales/blob/main/2020_Year_Of_Reckoning.pptx

Data Organization: Project data is separated into four folders: "COVID_data", "Govt_Data", "CAR_sales_data", and "Stock_Data".

Code organization: "Working_Notebooks" is a folder containing the individual workbooks of team members. These notebooks were merged into a file named "Working_Master". Plot formatting changes were made in the Working_Master along with minor edits. The images from the plots were saved in a folder named "Images". The "Working_Master" was copied as "Master_Notebook". Unused plots and code were culled.

2. Objective

Project examines factors affecting the change in car sales between 2019 and 2020 utilizing real world data, python, pandas, matplotlib and jupyter notebook.

This project demonstrates how Jupyter Notebook, Matplotlib can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
• pip for dependencies
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/danawoodruff/Car-Sales-Analysis.git
cd Car-Sales-Analysis

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by danawoodruff and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.