This project performs an exploratory data analysis (EDA) on an e-commerce sales dataset to uncover trends, sales performance, and other key insights. The notebook uses Python libraries such as Pandas and Plotly for data processing and visualization.
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Identifying Sales Trends: Understand peak and low sales periods for better inventory and marketing decisions.
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Customer Behavior Insights: Analyze purchasing patterns based on time and region.
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Profitability Analysis: Determine which products or categories drive the most revenue.
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Optimizing Shipping Strategies: Compare order and shipping dates to improve logistics.
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Data-Driven Decision Making: Helps businesses make informed strategies to boost revenue and efficiency.
Programming Language: Python Libraries: Pandas, Plotly Data Format: CSV Development Environment: Jupyter Notebook 🦭