Visual Analytics Tutorial: Selection Tools

PCX selection tools allow the designer to highlight and bring to focus individual datapoints as well as subsets of the loaded dataset. These features help in identifying trends and patterns in the data and decluttering the display. 

Select Axis: Highlight axes by clicking on them.

Select Datapoint: Highlight an individual point from the dataset by clicking anywhere on the plotted polyline. Values of selected datapoints can be adjusted via dragging on the axes (multiple values can be adjusted simultaneously, preserving the ratio between them, if multiple axes are selected).

Interval Selection: Bring a subset of the data into focus by applying an upper and lower bounds to the values of a dimension by clicking on the axis. Any points with values within the interval bounds on the given dimension is highlighted, all others are greyed out. All interval selections can be moved over selected axes by dragging, retaining the ratio between the bounds.

  • Select Bounds: First click on an axis sets the upper bound of the interval, the second click sets the lower bound.
  • Select Top Bounds: Set the upper bound only.
  • Select Bottom Bounds: Set the lower bound only.
  • Exact Interval: Set the exact numeric interval values (popup window).

Scatter Plot: Launches a new window with an auxiliary method for making selections. The datapoint values for a selected pair of dimensions are plotted on an XY graph, the dimensions for the X and Y axes are selected via drop-down menus. The designer can make free-form polygon selections by clicking on the Scatter Plot and any points included in the resulting polygon are brought into focus. The polygon selections can be dragged across the graph and deleted via buttons. Multiple scatter plots can be active simultaneously.

Previous/Next Selection: Switch to the previous/next selection screen of the main Parallel Coordinates plot. This allows the designer to make different simultaneous sets of selections for comparison and contrasting of identified patterns and subsets of data.