Here, we present ChemPlot, a Python library for chemical space visualization. ChemPlot is free and its source code is available on GitHub under the Berkeley Source Distribution (BSD) license. ChemPlot is a user-friendly software, in which users can transform their datasets into interactive 2D chemical space visualizations. The current version (1.2.0) of ChemPlot provides three dimensionality reduction methods: PCA, t-SNE, and UMAP. Additionally, two similarity methods are supported: structural and tailored. According to our knowledge, ChemPlot is the first tool that applies tailored similarity , which measures the similarity of molecules in a supervised manner considering the target properties of compounds, and thus provide a way to deal with the APC problem. Additionally, to better quantify the target property difference between molecules that are close to each other in a chemical space, we devise a new metric called the Distance Property Relationship (DPR) scores. ChemPlot can be installed via well-known Python package managers, including Conda and PyPI (pip). Finally, alongside the user manual that contains practical information and examples, we also provide a web interface to encourage the use of ChemPlot without the need for coding expertise (see Code Availability).