📚 Analyze-Best-Selling-Amazon-Books

This project analyzes the best-selling Amazon books dataset using Python and pandas. It provides insights such as top authors by the number of books listed, average ratings by genre, and basic data exploration.

✨ Features

1. 📊 Data Loading and Exploration:

   • Load the dataset from a CSV file.
   • Display the first 5 rows of the dataset.
   • Show the shape and column names of the dataset.
   • Provide summary statistics for numerical columns.

2. 🛠️ Data Cleaning:

   • Remove duplicate entries.
   • Rename columns for better readability (e.g., "Name" to "Title", "Year" to "Publication Year", "User Rating" to "Rating").
   • Convert the "Price" column to a float data type.

3. 📈 Analysis:

   • Identify the most popular authors by counting the number of books they have listed.
   • Calculate the average rating for each genre.

4. 💾 Export Results:

   • Save the top 10 most popular authors to a CSV file (top_authors.csv).
   • Save the average rating by genre to a CSV file (avg_rating_by_genre.csv).

📂 Files

• main.py: Contains the Python script for data analysis.
• bestsellers.csv: The dataset of best-selling Amazon books (not included in this repository).
• top_authors.csv: Output file containing the top 10 authors by the number of books listed.
• avg_rating_by_genre.csv: Output file containing the average rating by genre.

🛠️ Requirements

• Python 3.x
• pandas library

▶️ How to Run

1. Clone the repository and navigate to the project directory.
2. Place the bestsellers.csv file in the Analyze Best Selling Amazon Books folder.
3. Run the main.py script:

   python main.py

4. Check the output files (top_authors.csv and avg_rating_by_genre.csv) in the same folder.