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Walmart Sales Forecasting

Introduction

This project aims to identify various patterns and features that impact Walmart's sales and demand. By deriving key insights that influence sales, we develop a predictive model to forecast future demand.

Directory Structure

├── data
│   ├── Walmart_Store_sales.csv            # The raw dataset used for analysis and modeling.
│   ├── Walmart_Store_sales_updated.csv    # Final dataset after data preprocessing and feature engineering.
│   └── data_description.txt               # Description of the dataset.
├── notebooks
│   ├── 01_Walmart_Sales_Introduction_and_EDA.ipynb # Data exploration, preprocessing, and initial EDA.
│   ├── 02_Walmart_Sales_SQL_Analysis.ipynb        # Data analysis using SQL.
│   └── 03_Walmart_Sales_Model_Development.ipynb   # Feature engineering, model development, model enhancement, hyperparameter tuning, and evaluation.
├── README.md                                # Project documentation and overview.
├── requirements.txt                         # List of dependencies and required packages.
└── LICENSE                                  # License for the project.

Overview

  • Data Analysis: Conducted comprehensive exploratory data analysis (EDA) to uncover purchasing patterns and identify peak sales periods.
  • SQL Analysis: Leveraged SQL for advanced data queries and extracting key insights.
  • Feature Engineering: Implemented feature engineering techniques to enhance model performance.
  • Predictive Modeling: Developed and evaluated multiple predictive models to forecast future sales. The tuned model achieved an R² score of 0.9751.
  • Data Visualization: Generated a variety of plots and charts to facilitate better understanding and communication of the data.

Tech Stack

  • Python
  • SQL (SQLAlchemy)
  • Jupyter Notebooks
  • Pandas
  • NumPy
  • Scikit-learn
  • Matplotlib
  • Seaborn
  • Git

Setup

  1. Clone the repository:

    git clone https://github.com/Hrishikesh-Papasani/Walmart-Sales-Forecasting.git
cd Walmart-Sales-Forecasting

  2. Install the required packages:

    pip install -r requirements.txt

License

This project is licensed under the MIT License - refer LICENSE for details.

Acknowledgements

The dataset used in this project is sourced from Kaggle: Walmart Dataset.

Thanks to the open-source community for providing useful libraries and tools.

Contact

Please contact for more information

Mail: [email protected]

LinkedIn: LinkedIn