The purpose of this project was to analyze a car dataset and determine what a good price is for different makes, models, and odometer readings.
I got the data from Kaggle. The dataset is used car data from Craigslist. It contains 25 columns and 458,213 rows.
I am currently dreaming of buying a truck, and I want to make sure that when I do, I get a good car for a good price.
Below is a link to my software demo video.
Question: What is a good price for a Toyota Tacoma with 100,000 miles on it? Answer: Typically, a Toyota Tacoma with 100,000 miles on it is listed for $20,000. Anything below $15,000 is a good deal.
Question: What is an equivalent price for a Ford truck? Answer: Fords tend to sell for a little more, at around $24,000.
I used VSCode and Python 3.10 to develop this project.
The pandas, plotly, and dash libraries were essential to this project. I also used the Flatly bootstrap theme.
These websites helped me as I worked on this project:
- List specific questions and answers on the app
- Get user input (slider) on mile range
- Combine the two callbacks into one to avoid duplication