Apple iPhone Data Analysis Project

Overview

This is a complete Python data analysis project on Apple iPhone models from iPhone 1 (2007) to iPhone 17.

The project is structured for final-year academic submission and includes:

• Structured dataset creation using pandas
• Sales, revenue, and profit analysis
• Visualization and interpretation
• Feature impact insights (Face ID, 5G, Dynamic Island, USB-C)
• Strategic recommendations for iPhone 18

Project Structure

• apple_iphone_data_analysis.py: Main analysis script
• iphone_models_1_to_17.csv: Generated iPhone dataset
• outputs/iphone_financial_summary.csv: Computed financial summary
• outputs/plots/: Saved plots

Dataset Columns

• Model Name
• Launch Year
• Display Size
• Processor
• Camera Specifications
• Battery Capacity
• Special Features
• Launch Price
• Estimated Production Cost
• Units Sold (in millions)

Financial Formulas

• Revenue = Units Sold x Launch Price
• Profit = (Launch Price - Production Cost) x Units Sold

Note: Units are in millions; therefore revenue and profit in the script are reported in USD millions/billions.

Required Libraries

• pandas
• numpy
• matplotlib
• seaborn

How To Run

python apple_iphone_data_analysis.py

Generated Visuals

The script saves the following charts in outputs/plots/:

1. Sales trend over years (line chart)
2. Top-selling models (bar chart)
3. Profit comparison by model (bar chart)
4. Correlation heatmap

Academic Notes

• The script prints clear section-wise insights and interpretations.
• iPhone 16 and iPhone 17 entries are modeled as realistic analytical estimates for continuity.
• Production cost values are estimated for academic analysis.