Car-Purchasing

Business Intelligence application for supporting the decision making for the process of purchasing a car.

Overview

This application provides an interactive web-based dashboard for analyzing car purchasing data. It uses Python with pandas for data manipulation, matplotlib for visualizations, and Streamlit for the web interface.

Features

• 📊 Interactive data grids with filtering capabilities
• 📈 Multiple chart types including histograms, scatter plots, pie charts, and bar charts
• 🔍 Advanced filtering by gender, age, country, and salary range
• 💡 Key metrics and statistical summaries
• 📥 Export filtered data to CSV
• 🎨 Multiple visualizations for data exploration

Installation

1. Clone the repository:

git clone https://github.com/CezarConstantinescu/Car-Purchasing.git
cd Car-Purchasing

2. Install required dependencies:

pip install -r requirements.txt

Usage

Run the Streamlit application:

python -m streamlit run app.py

The application will open in your default web browser at http://localhost:8501.

Data Structure

The application uses a CSV file (car_sales.csv) with the following columns: -Salesperson -Customer Name -Customer Age -Customer Gender -Income -Income Type -Education Type -Family -Status -Housing Type -Family Members -Car Make -Car Model -Car Year -Sale Price -Payment Method -Sales Region -Sale Month -Day of Week -Season -Fuel Type -Transmission -Color -Owner -Engine -Max Power -Max Torque -Drivetrain -Seating Capacity -Fuel Tank Capacity

Dashboard Features

Filters

Use the sidebar to filter data by:

• Gender
• Age Range
• Country
• Annual Salary Range

Key Metrics

View important metrics including:

• Total number of customers
• Average car purchase amount
• Average annual salary
• Average net worth

Visualizations

• Car Purchase Amount Distribution: Histogram showing the distribution of purchase amounts
• Gender Distribution: Pie chart showing customer gender breakdown
• Age vs Car Purchase Amount: Scatter plot showing relationship between age and purchase amount
• Annual Salary vs Car Purchase Amount: Scatter plot showing correlation between salary and purchase
• Top 10 Countries: Bar chart of countries by average purchase amount
• Age Group Analysis: Bar chart showing average purchase by age group
• Net Worth vs Purchase Amount: Scatter plot colored by age

Data Export

Download filtered data as CSV for further analysis.

Technologies Used

• Python 3.x
• pandas - Data manipulation and analysis
• matplotlib - Data visualization
• streamlit - Web interface
• numpy - Numerical computing