This Python project focuses on analyzing Diwali sales data to gain insights that can be used to enhance customer experience and boost sales. The project utilizes various data analysis techniques to uncover patterns, trends, and key metrics related to Diwali sales.
Diwali is a significant festival, and analyzing sales data during this period can provide valuable insights for businesses. This project aims to harness the power of Python and data analysis libraries to:
- Understand customer behavior during Diwali.
- Identify popular products and categories.
- Analyze sales trends and patterns.
- Provide actionable insights for improving customer experience and increasing sales.
- Data cleaning and preprocessing.
- Exploratory data analysis (EDA) to uncover patterns.
- Visualization of sales trends using matplotlib and seaborn.
- Statistical analysis to identify significant factors.
- Recommendations for improving customer experience and sales.
# Clone the repository:
git clone https://github.com/iamtanmay07/diwali-sales-analysis.git
# Navigate to the project directory:
cd diwali-sales-analysis
# Install the required dependencies:
pip install -r requirements.txtThe main analysis is carried out in Jupyter notebooks within the notebooks directory. Each notebook focuses on a specific aspect of the Diwali sales data analysis, such as data cleaning, exploratory data analysis, visualization, and recommendations.
The main analysis is carried out in Jupyter notebooks within the notebooks directory. Each notebook focuses on a specific aspect of the Diwali sales data analysis, such as data cleaning, exploratory data analysis, visualization, and recommendations.
The project results include actionable insights and recommendations that businesses can leverage to enhance customer experience and improve sales during the Diwali festival.
This project is licensed under the MIT License - see the LICENSE.md file for details.