Plots

Plots are the centerpiece of the element view sidebar, allowing you to visualize distributions of attribute values and compare attributes between different elements and intersections. There are 3 available plot types: scatterplots, histograms, and KDEs. Scatterplots visualize individual elements across 2 attribute axis, allowing you to view correlations between attributes, whereas histograms and KDEs show distributions of attribute values.

By default, the plots visualize attributes and elements for all visible intersections in a grey color (visible intersections are ones present in the plot, but they may be scrolled off the top or bottom of the page). However, all 3 plot types are influenced by the currently selected and bookmarked intersections. The colors assigned to intersections by selection & bookmarking are reflected in the charts: points in the scatterplot take on the color of the intersection they belong to, and additional colored bars and lines appear showing distributes within intersections. For details, see the page for each plot.

Selections can be made graphically over plots; see Graphical Selection.

Plots are added via a header button; see Adding Plots. Plots can be removed by right-clicking and selecting Remove Plot from the context menu.

📄️ Adding Plots

By default, you'll see a bar chart for each numeric attribute in your dataset. However, you can add as many plots to the sidebar as you'd like. To add a plot, click the Add Plot button to open the add plot dialog:

📄️ Scatterplot

Scatterplots plot all elements in the visible intersections along two user-defined attribute axis.

📄️ Histogram

Histograms take all values for a particular attribute (from elements in visible intersections), sort them into bins,

📄️ Kernel Density Estimate (KDE)

Kernel Density Estimate Plots (also known as density plots or KDEs) show the probability density function for a given attribute.