📱 Apple iPhone Product Analysis 📊

Overview

This project analyzes Apple iPhone product data from Flipkart, exploring various aspects such as pricing, ratings, and reviews. The analysis is conducted using Python, pandas, matplotlib, and seaborn.

🛠️ Tools and Libraries Used

• Python 3.x
• pandas
• matplotlib
• seaborn

📋 Dataset

The dataset (apple_products.csv) contains information about various Apple iPhone models, including:

• Product Name
• Sale Price
• MRP (Maximum Retail Price)
• Discount Percentage
• Number of Ratings
• Number of Reviews
• Star Rating
• RAM
• Model Name

🔍 Key Analyses

1. Data Overview: Examining the structure and basic statistics of the dataset.
2. Price Analysis:
   • Identifying the highest and lowest priced products
   • Analyzing products within specific price ranges
3. Model Extraction: Creating a new 'Model Name' column from the product name
4. Rating Analysis:
   • Distribution of star ratings
   • Identifying top-rated products
5. Review Analysis: Finding products with the highest number of reviews
6. Discount Analysis: Identifying products with the highest discount percentages

📊 Visualizations

• Histogram of star ratings distribution
• (Additional visualizations can be added based on the analysis)

🚀 Key Findings

1. The price range of Apple iPhones in the dataset is from ₹39,900 to ₹149,900.
2. The average sale price for Apple products is ₹80,073.89.
3. iPhone SE models dominate the top 5 list for the highest number of reviews.
4. The highest discount percentage observed is 29% for the iPhone 11 Pro (Midnight Green, 64 GB).

🤝 Ending Note

Feel free to review the code and explore the analysis. If you have any suggestions or improvements, please don't hesitate to open an issue or submit a pull request. We're happy to accept changes that enhance the project!