Gridded Data#

hvPlot provides one API to explore data of many different types. Previous sections have exclusively worked with tabular data stored in pandas (or pandas-like) DataFrames. The other most common type of data are n-dimensional arrays. hvPlot aims to eventually support different array libraries but for now focuses on xarray. XArray provides a convenient and very powerful wrapper to label the axis and coordinates of multi-dimensional (n-D) arrays. This user guide will cover how to leverage xarray and hvplot to visualize and explore data of different dimensionality ranging from simple 1D data, to 2D image-like data, to multi-dimensional cubes of data.

For these examples we’ll use the North American air temperature dataset:

import xarray as xr
import hvplot.xarray  # noqa

air_ds = xr.tutorial.open_dataset('air_temperature').load()
air = air_ds.air