PythonPandasPlotlySeaborn
E-commerce Sales Data Analysis
Uncovered revenue trends, seasonal patterns, and top-performing categories across multi-dimensional sales data.
📊 Multi-dimensional sales insights
Dataset
E-commerce transactional dataset covering orders, products, categories, timestamps, and customer segments.
Methodology
- 1EDA with Pandas: trend, seasonality, and category breakdowns.
- 2Interactive Plotly visualizations for executive review.
- 3Seaborn statistical plots for technical deep-dives.
- 4KPI storytelling for both technical and non-technical stakeholders.
Final Outcome
Clear, decision-ready report on which categories to push, when seasonal peaks happen, and where margin is being left on the table.
Skills Used
PandasMatplotlibSeabornPlotlyEDAStorytelling