In the vibrant market of pre-owned vehicles, making informed decisions is key for both buyers and sellers. Our interactive dashboard serves as a beacon for navigating through the complexities of used car transactions across the United States. Whether you are in the business of selling cars, a prospective buyer, or a data enthusiast, our dashboard provides rich insights into sales trends, pricing, and much more.
The motivation behind this project stems from the need to understand the used car market dynamics at a glance. We solve the problem of scattered information by centralizing transaction data into a user-friendly visual interface, highlighting critical market trends and enabling data-driven decision-making.
Our project unfurls as a comprehensive dashboard detailing used vehicle sales from eBay within the US. Designed as a navigational tool through the American pre-owned car landscape, this dashboard is crafted to empower both dealerships and private sellers with data-driven insights for strategic pricing and inventory management, bolstering successful business outcomes. Enriched with data segmentation by brand, model, body style, mileage, and price, the platform further provides a window into the geographical spread of vehicles via spatial analysis. Amidst the supply chain challenges wrought by the COVID-19 pandemic, our goal is to streamline access to key performance indicators and market intelligence, aiding entrepreneurs in making informed decisions within a dynamic environment.
Dive into a sea of data with just a few clicks:
- Explore transaction counts via a heat map of the US.
- Discover pricing distributions with interactive histograms.
- Filter data based on state, make, mileage, and more to find exactly what you're looking for.
- Analyze trends over the years with our trend lines.
For a live experience, visit our deployed dashboard.
👀 Interested in seeing our dashboard in action? Check out our demo for a quick tour!
Need support? Feel free to [open an issue] on our repository, and we'll assist you promptly.
If you're looking to run the app locally or wish to contribute, we welcome your interest and input! Here's
- Clone the repository to your local machine.
git clone https://github.com/UBC-MDS/DSCI-532_2024_8_DriveDeepDive.git- Navigate to the project directory and create conda envrionment:
conda env create -f environment.yml- Activate the new environment:
conda activate DriveDeepDive- Launch the dashboard locally:
python src/app.pyFor more information on contributing, please refer to our contributing guidelines.
Thank you for visiting our project, and we look forward to your valuable contributions and feedback!
Charles Xu, Chris Gao, Alan Powichrowski and Doris Wang