https://github.com/robson-python/data-analysis-car-price-prediction

This dataset contains 10,000 entries created for the purpose of predicting car prices.
https://github.com/robson-python/data-analysis-car-price-prediction

data data-visualization dataanalysis inteligencia-artificial machine-learning matplotlib pandas-dataframe python scikit-learn seaborn vscode

Last synced: 3 months ago
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This dataset contains 10,000 entries created for the purpose of predicting car prices.

• Host: GitHub
• URL: https://github.com/robson-python/data-analysis-car-price-prediction
• Owner: Robson-Python
• License: gpl-3.0
• Created: 2025-02-14T19:06:32.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2025-02-14T19:16:22.000Z (12 months ago)
• Last Synced: 2025-02-14T20:22:31.619Z (12 months ago)
• Topics: data, data-visualization, dataanalysis, inteligencia-artificial, machine-learning, matplotlib, pandas-dataframe, python, scikit-learn, seaborn, vscode
• Language: Jupyter Notebook
• Homepage:
• Size: 1.07 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Data-Analysis-Car-Price-Prediction

Car Price Prediction Data Analysis

Project

This dataset contains 10,000 entries created for the purpose of predicting car prices. Each row represents information about a car and its price.

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Dataset:

Make: Specifies the make of the car (e.g. Toyota, BMW, Ford).

Example values: "Toyota", "BMW", "Mercedes".

Model: Specifies the model of the car (e.g. Corolla, Focus, X5).

Example values: "Corolla", "Focus", "X5".

Year: The year the car was produced. Newer years generally indicate higher prices. Example values: 2005, 2018, 2023.

Engine_Size: Specifies the engine size in liters (L). Larger engines generally correlate with higher prices.

Example values: 1.6, 2.0, 3.5.

Fuel_Type: Indicates the type of fuel used by the car:

Gasoline: Cars that run on gasoline.

Diesel: Cars that run on diesel fuel.

Hybrid: Cars that run on both gasoline and electricity.

Electric: All-electric cars.

Transmission: The type of transmission in the car:

Manual: Manual transmission.

Automatic: Automatic transmission.

Semi-Automatic: Semi-automatic transmission.

Mileage: The total distance traveled by the car, measured in kilometers. Lower mileage generally indicates a higher price.

Example values: 15,000, 75,000, 230,000.

Doors: The number of doors on the car. Typically 2, 3, 4, or 5 doors.

Example values: 2, 3, 4, 5.

Owner_Count: The number of previous owners of the car. Fewer owners usually indicate a higher price.

Example values: 1, 2, 3, 4.

Price: The estimated selling price of the car. It is calculated based on several factors, such as year of production, engine size, mileage, fuel type, and transmission.

Example values: 5,000, 15,000, 30,000.

Data Source

This dataset was made available by Tech on Kaggle and is licensed under Other:

> Tech, Airplane Price Dataset.

> Available at: [Kaggle Dataset Link](https://www.kaggle.com/datasets/asinow/car-price-dataset/data)

The objective of this project is to train and put my skills into practice. I will also include it in my portfolio so I can showcase my skills and win future projects and clients in the area of ​​Data Analysis and Science with Python.

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Software and equipment used for development: Python 3.12.8 - Libraries (Pandas, Numpy, Matplotlib, Seaborn, scikit-learn)

Operating system: Windows 11 Home Single Language.

Computer: HP 256 G9 - Intel Core i3.

Data Analysis and Machine Learning

© 2025 - by Robson Silva - Python Programmer and Data Analyst.