This project provides a comprehensive analysis of super store sales data using Python. The goal is to derive actionable insights to inform business decisions, identify trends, and optimize sales strategies. Features Data Cleaning & Preprocessing: Handling missing values, data normalization, and data type conversion. Exploratory Data Analysis (EDA): Identifying key patterns and trends in sales data through visualizations and descriptive statistics. Product Performance Evaluation: Analyzing product categories and individual items to identify top performers and underperformers.
Technologies Used Programming Language: Python Data Manipulation: Pandas, NumPy Visualization: Matplotlib