2.5 2D frequencies

2.5.1 Rectangular binning in plotly.js

The plotly package provides two functions for displaying rectangular bins: add_heatmap() and add_histogram2d(). For numeric data, the add_heatmap() function is a 2D analog of add_bars() (bins must be pre-computed), and the add_histogram2d() function is a 2D analog of add_histogram() (bins can be computed in the browser). Thus, I recommend add_histogram2d() for exploratory purposes, since you don’t have to think about how to perform binning. It also provides a useful zsmooth attribute for effectively increasing the number of bins (currently, “best” performs a bi-linear interpolation, a type of nearest neighbors algorithm), and nbinsx/nbinsy attributes to set the number of bins in the x and/or y directions. Figure 2.30 compares three different uses of add_histogram(): (1) plotly.js’ default binning algorithm, (2) the default plus smoothing, (3) setting the number of bins in the x and y directions. Its also worth noting that filled contours, instead of bins, can be used in any of these cases by using histogram2dcontour() instead of histogram2d().

p <- plot_ly(diamonds, x = ~log(carat), y = ~log(price))
  add_histogram2d(p) %>%
    colorbar(title = "default") %>%
    layout(xaxis = list(title = "default")),
  add_histogram2d(p, zsmooth = "best") %>%
    colorbar(title = "zsmooth") %>%
    layout(xaxis = list(title = "zsmooth")),
  add_histogram2d(p, nbinsx = 60, nbinsy = 60) %>%
    colorbar(title = "nbins") %>%
    layout(xaxis = list(title = "nbins")),
  shareY = TRUE, titleX = TRUE