This project visualizes car advertisement data from one data set containing information on over 50k cars available for sale. It includes interactive visuals for exploring the number of vehicle types by make, condition vs model year, comparing the price distribution between two makes, the average cost by make, the price distribution by make for all makes, average cost by model year, and cost by condition.
👩🏽💻 Command line 🪐 Jupyter Notebook 🕸️ Web API 🏗️ Web Application Building 👩🏽💻 Development Environment 🐍 Anaconda Distribution 📂 File-IO 🐍 Intermediate Python
- This project uses pandas, streamlit, plotly-express, and matplotlib. It requires python 3.11.
- To run the project on your local machine:
streamlit run app.py - To view it online: Click Here