Building a Quick Commerce Inventory Optimization Dashboard with Dash, Plotly, and Pandas
Introduction In this blog, we’ll build a data-driven dashboard to visualize product demand trends and suggest optimal inventory plans for quick commerce operations using historical order data. The project leverages Python's Dash framework, Plotly for interactive visualizations, and Pandas for data processing. By the end, you’ll learn how to: Load and preprocess demand and inventory data Create interactive dropdown filters Visualize historical order trends and optimized stock levels Build and run a full-fledged web dashboard with Dash. Prerequisites Before diving in, ensure you have the following: Basic knowledge of Python and Pandas Familiarity with Dash and Plotly Installed packages: dash , pandas , plotly Step 2: Load and Inspect the Data Step 3: Initialize the Dash App Step 4: Define the Layout Step 5: Build the Callback Function Step 6: Filter & Aggregate the Data 📈 Demand Trend Chart 📊 Inventory Plan Chart Step 7: Run the App Summary In the fast-p...
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