In molecular data science, the complex variability of molecular data, as stored in high-dimensional spaces spanned by graphs, textual representation, atom coordinates, or any combinations thereof, demands the development of chemically informative data visualization methods and tools. The data visualization provides a practical means to reduce the high-dimensional molecular data to spaces of two (2D) or three dimensions (3D). A visual inspection of data in low-dimensional chemical space enables a more realistic screening of molecules with user-desired properties, in addition to exploratory analysis of the data including, but not limited to, diversity and outlier detection.