What type of plot visually represents data values using varying shades of color on a matrix?

A heatmap is an effective visual representation of data values using varying shades of color in a matrix format. This type of plot allows for the easy visualization of complex data sets by indicating the intensity of values through color gradients. The colors can range from light to dark or follow a specific color scale, making it straightforward to identify patterns, correlations, or concentrations of data values at a glance.

In scenarios where large datasets are involved, heatmaps are particularly useful because they can condense information into a more digestible format compared to other plot types. For instance, heatmaps are commonly used in fields such as biology for gene expression data, in business for displaying metrics over time, and in various forms of statistical analysis.

Other options are not suited to represent data in this manner. Line graphs represent data points connected by lines, which is effective for showing trends over time but does not convey the density of data values like heatmaps do. Bar charts display categorical data with rectangular bars, providing clear comparisons of quantities, but they do not use color gradients to represent density or variation within a matrix format. Scatter plots show relationships between two continuous variables, illustrating individual data points rather than summarizing data in a matrix with color shading.