https://github.com/neha1399/amazon-product-recommendation

https://github.com/neha1399/amazon-product-recommendation

glob numpy pandas python

Last synced: 3 months ago
JSON representation

• Host: GitHub
• URL: https://github.com/neha1399/amazon-product-recommendation
• Owner: neha1399
• Created: 2024-12-17T04:06:37.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-22T14:21:10.000Z (over 1 year ago)
• Last Synced: 2025-06-19T06:51:18.102Z (about 1 year ago)
• Topics: glob, numpy, pandas, python
• Language: Jupyter Notebook
• Homepage:
• Size: 38.1 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

Awesome Lists containing this project

README

          
# Amazon Product Ratings Analysis

---

## Overview

This project analyzes Amazon product ratings from multiple datasets and generates insights in both tabular and visual formats. The analysis includes:

1. **Average Ratings by Category**

2. **Total Number of Ratings by Category**

3. **Top 5 Products by Ratings in Each Category**

Additionally, the project creates interactive visualizations using Plotly to represent the data effectively.

---

## Features

1. **Data Processing**:

   - Combines multiple datasets of product ratings.

   - Handles inconsistencies such as missing values or invalid data types.

   - Ensures uniform column names across datasets.

2. **Analysis**:

   - Calculates average ratings for each category.

   - Identifies the total number of ratings per category.

   - Extracts the top 5 products by ratings for each category.

3. **Visualizations**:

   - **Bar Chart**: Average ratings by category.

   - **Bar Chart**: Total number of ratings by category.

   - **Table**: Top 5 products with their categories, ratings, and number of ratings.

   - **Pie Chart**: Distribution of ratings across categories.

---

## Files

1. **Scripts**:

   - `analysis.py`: Main script for data analysis and visualization.

   - `visualizations.py`: Contains functions to generate visualizations using Plotly.

2. **Input**:

   - CSV files containing Amazon product data, stored in the `notebooks/data/` directory.

3. **Output**:

   - CSV files saved in the `output/` directory:

     - `average_ratings_by_category.csv`

     - `total_ratings_by_category.csv`

     - `top_5_by_category.csv`

   - Interactive visualizations displayed in the browser.

---

## Visualizations

1. **Bar Chart (Average Ratings)**:

   Displays the average ratings for each product category.

2. **Bar Chart (Total Ratings)**:

   Shows the total number of ratings for each category.

3. **Table**:

   Lists the top 5 rated products for each category, with columns:

   - Product Name

   - Category

   - Rating

   - Number of Ratings

4. **Pie Chart (Ratings Distribution)**:

   Illustrates the proportion of ratings contributed by each category. The highest-rated category is highlighted.

---

## Dependencies

- **Pandas**: Data manipulation and processing.

- **NumPy**: Numerical operations.

- **Plotly**: Interactive visualizations.

- **glob**: File pattern matching for multiple datasets

- **OS**: File and directory management.