Used Cars Dataset EDA

Exploratory Data Analysis and Market Analysis of a dataset of used cars
Explore the docs »

Report Bug · Request Feature

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact

About The Project

In this exploratory data analysis (EDA), we will use the 'Used Cars' dataset from Kaggle (https://www.kaggle.com/datasets/austinreese/craigslist-carstrucks-data) to gather as much information as possible about the data.

Subsequently, after completing the dataset cleaning, we will conduct a small business simulation exercise with the remaining cars. In this exercise, we will simulate owning all these cars and outline a small business strategy for a rental/leasing company.

(back to top)

Built With

• 
• 
• 

(back to top)

Getting Started

• images: a folder containing the images used in the Jupyter notebook.
• Used_Cars_EDA.ipynb: a Jupyter notebook that includes the entire exploratory data analysis, along with markdown comments explaining the entire process.
• README.md: this file.

Prerequisites

It is essential to have the working dataset downloaded and ready: https://www.kaggle.com/datasets/austinreese/craigslist-carstrucks-data.

Usage

The Jupyter notebook is ready to be downloaded and executed.

(back to top)

Roadmap

• Initial Data Distribution Analysis
• Standard Data Cleaning
  • Removal of Erroneous Data
  • Outlier Removal
  • Handling of NaN Values
• Feature relation analysis
• Business Conclusion
• Implementation of a regression model to calculate the optimal selling price of vehicles
• Usage of advanced data cleaning techniques
  • Recovery of erroneous or anomalous data

See the open issues for a full list of proposed features (and known issues).

(back to top)

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

(back to top)

License

Distributed under the MIT License. See LICENSE.txt for more information.

(back to top)

Contact

Javier Requena - GitHub - [email protected]

Project Link: https://github.com/Javier-Requena/UsedCars-EDA-python

(back to top)