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import hvplot.xarray  # noqa

Similar to image, contourf displays values on a 2d grid. But it first segments data into various levels.

import xarray as xr

ds = xr.tutorial.open_dataset('air_temperature')
Dimensions:  (lat: 25, time: 2920, lon: 53)
  * lat      (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0
  * lon      (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0
  * time     (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00
Data variables:
    air      (time, lat, lon) float32 ...
    Conventions:  COARDS
    title:        4x daily NMC reanalysis (1948)
    description:  Data is from NMC initialized reanalysis\n(4x/day).  These a...
    platform:     Model

There are lots of options exposed to control the style and contents of the contourf plot:

ds.mean(dim='time').hvplot.contourf(z='air', x='lon', y='lat', levels=20,
                                    clabel='T [K]', label='Mean Air temperature [K]',

Geographic Data#

ds.hvplot.contourf(levels=20, geo=True, coastline=True, widget_location='left_top')
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Download this notebook from GitHub (right-click to download).