This project aims to create a data-driven interactive visualization that offers users a unique and immersive experience in exploring the world of cocktails. The project utilizes python and Selenium library to scrape down 100 cocktail recipes from online sources and collects data on their names, ingredients, glass types, shaking methods, decorations, and nutritional characteristics. The data is then exported into a CSV file and imported into Processing for visualization. The core feature of the project is the interactive filter bar, which allows users to pick cocktails based on their preferred content of Sour/Sugar, Alcohol, and Bitter. The filtered options are displayed on the upper part of the interface, and users can click on a cocktail name to view a diagram that represents the ingredient composition and making method. The flavor of the cocktail, such as cherry, peach, and violet, is also displayed on the bottom to provide additional information for users to make informed choices. This project showcases the potential of data visualization in enhancing the understanding and appreciation of cocktails and provides a platform for users to discover and experiment with new recipes and f lavors. The project offers a fun and educational experience for cocktail enthusiasts and provides insights into the essence of cocktails - the balance between Sour, Sugar, Alcohol, and Bitter.