Tables are effective as a compact and precise record, but they are less conducive to holistic communication or discovery of patterns. Researchers often resort to tables for reporting relationships among several variables or groups, or when reporting the results of statistical analyses. This tutorial discusses and demonstrates approaches to visualizing results in three situations that are relatively common in psychological science and where tables are often used: (1) factor analysis, (2) comparisons among multiple groups on multiple dimensions, and (3) multiverse analysis. The visualization strategies are implemented in R software (with ggplot2 and DiagrammeR packages), though they can also be implemented in other software. These visualizations trade off the compact precision of tables in favor a visual representation strategy that makes complex patterns more intuitive, both for exploratory purposes and for communicating results.