a7medm0sta / brazilian-ecommerce-ml

This project showcases a comprehensive data analysis and prediction pipeline using Python, R, and SQL. The focus is on sentiment analysis and stock market prediction, involving multiple tasks, from data exploration to predictive modeling.

Brazilian E-commerce ML

c This project focuses on geospatial analysis of Brazilian e-commerce data. The goal is to analyze and visualize various aspects of e-commerce transactions, including customer locations, order distributions, and other relevant metrics.

Project Structure

• geospatial-analysis-of-brazilian-e-commerce.ipynb: Jupyter Notebook containing the code for data analysis and visualization.
• .gitignore: Git ignore file to exclude unnecessary files from version control.
• README.md: This file.
• Schema.png: Image file depicting the schema of the data used in this project.

Data Schema

Requirements

• Python
• Jupyter Notebook
• pip

Setup

1. Clone the repository:

   git clone https://github.com/A7medM0sta/brazilian-ecommerce-ml.git
   cd brazilian-ecommerce-ml

2. Install the required packages:

   pip install -r requirements.txt

3. Open the Jupyter Notebook:

   jupyter notebook geospatial-analysis-of-brazilian-e-commerce.ipynb

Usage

Run the cells in the Jupyter Notebook to perform the geospatial analysis and visualize the results.

License

This project is licensed under the MIT License.