Mini Project β Excel to Python Bootcamp
Developer: Jeet Sengupta (Junior Data Analyst)
As a newly joined Junior Data Analyst at Amazon India, the Sales and Operations team provided a comprehensive sales transaction dataset spanning various Indian states, product categories, payment modes, and customer segments.
The objective of this project is to evaluate overall business performance, uncover regional and product-level inefficiencies, and provide data-driven insights to help management plan the upcoming quarter's strategy.
- Data Cleaning & Preprocessing: Programmatically handle missing data, remove duplicates, fix structural errors, and ensure correct data types using Python.
- Sales & Profitability Analysis: Evaluate financial performance metrics across time periods, states, and payment modes.
- Product Performance Evaluation: Identify top-performing categories and flag bleeding, underperforming products.
- Geographical Insights: Isolate underperforming regions across India to identify strategic choke points.
- Data Visualization & Dashboards: Create interactive or static visual dashboards to present complex trends simply.
- Strategic Recommendations: Formulate actionable business solutions based on data trends.
- Development Environment: Google Colab (Python 3)
- Data Manipulation: Pandas, NumPy
- Data Visualization: Matplotlib, Seaborn
- File Management & Version Control: Git, GitHub, MS Excel (
.xlsx)
- Which product categories drive the highest revenue and profit margins?
- Which states or regions are underperforming and require operational restructuring?
- How do different payment modes impact order values or frequencies?
- What operational bottlenecks or low-margin items should be eliminated before next quarter?
This mini-project was completed as part of the curriculum for the Excel to Python Analytics Bootcamp hosted by DevTown.
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