Factors_influencing_price_of_vehicles

EDA project from Practicum by Yandex

Goal

Prepare a report for the Crankshaft List to determine whether age, mileage, condition, transmission type, and color influence the price of a vehicle based on the data collected over the last few years.

This project's repo includes the following files:

• The project's final jupyter notebook (Exploratory Data Analysis Project_final.ipynb);
• A pdf format of the notebook (Exploratory Data Analysis Project_final.pdf)
• Input data (vehicles_us.csv)
• Project description from Practicum (project description_price_of_vehicles.pdf)

This project includes the following steps:

1. Descriptive statistics;
2. Artifacts removal;
3. Missing values replacement;
4. Calculations;
5. EDA: outliers removal;
6. Analysis of connections between various features and the target variable.

Based on the analysis we have come to the following conclusions:

1. On average, the older a vehicle, the lower the price;
2. On average, the higher the mileage, the lower the price;
3. On average, the better the condition of a vehicle, the higher the price;
4. Vehicles with the 'other' type of transmission tend to be more expensive. It is probably explained by the fact these other types give more flexibility and comfort to the driver and more efficient in terms of fuel usage.
5. There is no clear connection between price and paint color, it depends mostly on customers' preferences. Interestingly, orange cars seem to be the most expensive, although their number is quite low in this data set (only 88 cars). Most cars are black and silver but they are not the most expensive.

The logbook of this project can be found here (Introduction to EDA tab).

Total time spent on the project: 32.6 hours with a daily average of 2.27 hours working for 14 days.