Brushing Scatter Plots
- Interactively select a region on a scatter plot to highlight the points contained within it.
- The selection (brush) is typically rectangular or circular and can be moved or resized to explore different areas.
- Useful for identifying trends, patterns, groups, and outliers that may not be obvious in a static plot.
Definition
Section titled “Definition”Brushing scatter plots is a visualization technique that allows users to interact with a scatter plot by highlighting specific data points or groups of data points. This technique is often used to explore and analyze data in more depth, and can be a useful tool for identifying trends, patterns, and outliers in a dataset.
Explanation
Section titled “Explanation”To brush a scatter plot, the user selects a region on the plot using a mouse or other input device. This selection typically appears as a rectangular or circular brush, and any data points within the brush are highlighted or emphasized. The user can manipulate the brush to explore different regions of the plot, and the highlighted data points update accordingly. By enabling dynamic, region-based selection and highlighting, brushing facilitates deeper interactive exploration of relationships within the data.
Examples
Section titled “Examples”Income vs. Education Level
Section titled “Income vs. Education Level”By brushing a region of a scatter plot where income is low and education level is high, the user can identify a group of data points that may represent individuals who are under-employed despite their education level. This information could be used to further investigate this trend and potentially identify solutions to the problem.
Age vs. Mortality Rate
Section titled “Age vs. Mortality Rate”By brushing a region of a scatter plot where age is high and mortality rate is low, the user can identify a group of data points that may represent individuals who have a lower than average mortality rate for their age group. This information could be used to further investigate factors that may be contributing to this trend, such as lifestyle choices or genetic factors.