In this study, we introduced ChemPlot, a Python library for chemical space visualization. When designing ChemPlot, we aimed to provide a straightforward library where coding would be smooth and intuitive. This was achieved by providing a simple code flow and naming, handling the function parameters automatically, and preparing a descriptive user manual. ChemPlot allows users to convert molecular data files into chemical space visualizations simply by using a few lines of code and without setting any input parameters. Moreover, we developed a web application to streamline the visualization of chemical spaces without the 0.11 0.11 0.11 0.12 0.11 0.12 0.10 0.11 0.12 0.12 0.13 0.12 0.13 0.12 0.14 0.13 0.15 0.12 BBBP 0. need of a coding background and essentially for daily use. Thus, the ChemPlot Python library alongside its user-friendly web application are designed to serve a broad community of users.