Used Cars Dataset EDA

Exploratory Data Analysis and Market Analysis of a dataset of used cars
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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.

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• 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.

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

The Jupyter notebook is ready to be downloaded and executed.

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• 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).

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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

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

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Javier Requena - GitHub - javier.requena@protonmail.com

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

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