# 3 Arranging multiple views

One technique essential to high-dimensional data analysis is the ability to arrange multiple views. Ideally, these views are linked in some way to foster comparisons (the next chapter discusses linking techniques). The next section, Arranging htmlwidgets describes techniques for arranging htmlwidget objects, which many R packages for creating web-based data visualizations build upon, including plotly. Typically interactivity is isolated within an htmlwidget object, but Linking views without shiny explores some more recent work on enabling interactivity across htmlwidget objects. The following section, Subplots describes the subplot() function, which is useful for merging multiple plotly objects into a single htmlwidget object. The main benefit of merging (rather than arranging) plotly objects is that it gives us the ability to synchronize zoom and pan events across multiple axes. The last section, Navigating many views discusses some useful tools for restricting focus on interesting views when there are more views than you can possibly digest visually.