Exploratory Data Analysis
The distribution of transaction amounts shows a strong right skew, indicating a majority of low-value transactions and a few high-value ones which could affect average metrics.
Most purchases are for small quantities, typically 1–3 units. Bulk orders are rare. This reflects common consumer purchasing behavior in retail
Profit values show with many near-zero values. This suggests thin profit margins and the possibility of many low-profit items or frequent discounts.
Phones and Chairs show consistently high profits, making them top-performing items. Binders, Tables, and Bookcases display negative or very low average profits, indicating potential loss-making areas or heavy discounting.
There’s no clear linear correlation between quantity and profit. Profitability may decline with larger orders — likely due to volume-based discounts.
Clothing stands out as a highly profitable category with a wide spread. Furniture shows inconsistent profits, with some losses, suggesting it needs further attention.
The treemap shows Phones and Chairs as dominant subcategories by sales. It visually identifies top revenue drivers and areas to focus on for marketing.
Monthly sales exhibit seasonality with repeating patterns. Peaks during certain months may correspond to sales campaigns, holidays, or budget cycles.
Daily profits show volatility with several negative profit days, indicating returns, discounts, or operational losses. Overall, there’s no consistent upward or downward trend.
