https://github.com/bhaveshbhakta/amazon-sales-data-visualization
Amazon Sales Data Visualization
https://github.com/bhaveshbhakta/amazon-sales-data-visualization
amazon-sales-data-analysis data-analysis data-preprocessing data-visualization machine-learning
Last synced: about 1 month ago
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Amazon Sales Data Visualization
- Host: GitHub
- URL: https://github.com/bhaveshbhakta/amazon-sales-data-visualization
- Owner: BhaveshBhakta
- Created: 2024-12-04T16:56:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-06T17:24:16.000Z (over 1 year ago)
- Last Synced: 2025-06-27T20:40:02.811Z (12 months ago)
- Topics: amazon-sales-data-analysis, data-analysis, data-preprocessing, data-visualization, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 808 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Amazon Sales Data Visualization
This project focuses on analyzing and visualizing Amazon sales data to uncover insights through various data visualization techniques. The dataset contains 1,426,337 rows with a size of 18,542,381. Using libraries like `matplotlib` and `seaborn`, we performed extensive data analysis and visualizations, providing insights into different aspects of the sales data.
## Project Overview
The project involves the following key steps:
1. **Exploratory Data Analysis (EDA)**: Initial exploration of the dataset to understand its structure and identify missing values, outliers, and key features.
2. **Pandas Profiling**: Utilized the pandas profiling library to perform automated exploratory data analysis and generate a comprehensive report.
3. **Data Visualization**: Implemented various visualizations to present insights into:
- **Descriptive Analysis**: Overview of key statistics of the data.
- **Comparative Analysis**: Comparison of sales data across different categories.
- **Category-wise Insights**: Insights into the sales performance of different product categories.
- **Monthly Analysis**: Examination of sales trends over different months.
- **Top-N Items**: Identifying top-selling items based on various metrics.
- **Correlation**: Analyzing the relationships between different numerical variables.
## Libraries Used
- `matplotlib`: For creating static, animated, and interactive visualizations.
- `seaborn`: For making attractive and informative statistical graphics.
- `pandas`: For data manipulation and analysis.
- `pandas_profiling`: For generating an EDA report.
## Data Source
Kaggle - https://www.kaggle.com/datasets/asaniczka/amazon-products-dataset-2023-1-4m-products
## Installation
To get started with the project, clone the repository and install the required dependencies:
```bash
git clone https://github.com/BhaveshBhakta/Amazon-Sales-Data-Visualization.git
cd Amazon-Sales-Data-Visualization
```
## Results and Insights
The project provides valuable insights into the sales patterns and trends of products sold on Amazon, helping to understand:
- Which categories are performing the best.
- Sales trends over different months.
- The correlation between different features such as price, sales volume, and category.
## Contributing
Feel free to fork this repository, contribute, or open issues for suggestions and improvements!