Online Retail Sales Analysis and Visualization

Project Overview

This project analyzes an online retail sales dataset to uncover key insights about sales trends, customer behavior, and product performance.

Dataset

• Source: UCI Machine Learning Repository.
• Description: The dataset includes transaction data from an online retail store.

Objective

The goal of this analysis is to:

• Explore sales trends over time.
• Identify top-selling products and key customer segments.
• Provide insights into customer purchasing patterns.
• Visualize sales performance through interactive dashboards.

Key Steps

1. Data Cleaning: Handled missing values and normalized categorical data.
2. Exploratory Data Analysis (EDA): Analyzed sales performance by time, product, and country.
3. Statistical Analysis: Performed correlation analysis and hypothesis testing.
4. Data Visualization: Visualized trends using PowerBI and Python.

Tools

• Python (Pandas, Matplotlib, Seaborn)
• PowerBI
• Excel

How to Run

1. Clone the repository:

   git clone https://github.com/vinayzende8/Online_Retail_sales_anlysis.git