Tools for visualising densities, both rough (binned histograms) and smooth (smooth density estimates).

All methods accept weights.

Binning data in 1d and 2d is tedious and tricky if you want to correctly deal with floating point (FP) issues. The `bin' package provides a convenient interface for break calculation and binning in 1d and 2d.

• bin_interval: interval bins (1d)
• bin_rect: rectangular bins (2d)
• bin_hex: hexagonal bins (2d)

This package also provides two methods for density estimation, kernel_density and local_density. local_density uses local regression as implemented in the locfit package, and provides a large number of options to control the output. However, it can be slow, so kernel_density provides a faster implementation that offers less control.

Both functions work with either 1d or 2d data, and both share a grid argument which specifies the locations where densities should be computed. This adds flexibility, allowing the function to be used to display the density over a regular grid, or just where the data points lie.