With the advent of the digital era, Grasshopper-based data visualization technology has been an emerging data representation method in recent years. It greatly improves the scientific accuracy, practical feasibility, and sustainable adaptability of the decision-making process and design results. It plays an irreplaceable role in urban planning and design as one of the basic visualization techniques for urban planners. This study outlines the development history of data visualization and the current application status of Grasshopper data visualization in urban planning and design, compares the basic process of data extraction and screening based on the Grasshopper platform, and compares urban data collection platforms, data formats, and data processing methods. Finally, the four-step process model of “data preparation, data integration, and structural processing, visualization model construction, visualization variable selection, and processing” is summarized and applied to two urban-scale visualization practices: “visualization of average annual household income data in London and UK” and “number and distribution of major tree species in London with corresponding household income visualization.” The Grasshopper-based data visualization results are highly expressive. They can be used for site context mining and dynamic data comparison, providing a data-driven foundation and scientific context for research. The extreme extensibility, programmability, and modifiability of data visualization using Grasshopper have good application prospects and development potential in the field of data-driven urban design and planning. Although Grasshopper has become more and more potent in recent years, it still has shortcomings in the field of data visualization that cannot be ignored. More researchers and developers are needed to further tap its potential and put it into practice.