Sales Data Insight Analysis

I need my historical sales data turned into clear, actionable insights that will directly improve day-to-day decision making. The raw files are already exported and ready for you—roughly two years of transaction-level records with product, region, and channel details.

Your toolkit must centre on Python with libraries (Pandas, NumPy). Please write clean, well-commented notebooks or scripts that:

• import and tidy the data
• perform exploratory and descriptive statistics to surface hidden patterns
• highlight drivers behind revenue shifts, seasonality, and outliers
• translate findings into concise recommendations that a non-technical manager can act on

A short executive summary (PDF or Markdown) and the fully reproducible code are the required deliverables. Charts are welcome where they clarify a point, but the emphasis is on depth of analysis rather than flashy dashboards. If you think additional lightweight visuals or a quick pivot in Excel could sharpen the narrative, feel free to include them.

I will consider the job complete when I can run your code end-to-end, reproduce every table or figure, and see a clear link between the analysis and practical decisions—pricing tweaks, stock-level adjustments, or regional focus, for example.