Office-Retailer-EDA

This dataset consists of 8399 records and 23 features of superstore transactions. The purpose of this analysis was to perform statistical queries and create visualization using python libraries. Libraries used: pandas, seaborn, matplotlib

There are seven queries and 14 visualizations in this analysis (7 in python using pandas, seaborn, matplotlib libraries and 7 in Tableau)

Visualization in Tableau

1. Discount percentage vs. Sales Amount (Query and Scatterplot Visualization)
2. Discount percentage by Sales Profitablity- Profit or Loss (Query and Scatterplot Visualization with Separation of Positive & Negative Profit)
3. Number of Sales by Order Date (Query and Line plot visualization)
4. Sales by Profit or Loss with Order date (Query and Line plot Visualization with Separation of Profit and Loss Markers)
5. Percentage of type of products sold by region (Query and Colorful Bar plot Visualizaiton)
6. Relationship between Profit, Sales and Shipping Cost
7. Order Quantity vs. Shipping Mode (Query and Boxplot Visualization)

Visualization in Tableau focuses on creating Dashboard for Sales by type of Sales, Sales by Item type, and Number of Sales quantity with different Shipping Mode.

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