hvPlot.image#

hvPlot.image(x=None, y=None, z=None, colorbar=True, **kwds)[source]#

Image plot

You can use image to display for example geographic data with independent latitude and longitude fields and a third dependent field.

Reference: https://hvplot.holoviz.org/reference/xarray/image.html

Parameters:

xstring, optional: The coordinate variable along the x-axis
ystring, optional: The coordinate variable along the y-axis
zstring, optional: The data variable to plot
colorbar: boolean: Whether to display a colorbar
kwdsoptional: To see all the keyword arguments available, run hvplot.help(‘image’). See Plotting Options for more information.

Returns:

holoviews.element.Image / Panel object

You can print the object to study its composition and run:

import holoviews as hv
hv.help(the_holoviews_object)

to learn more about its parameters and options.

References

Bokeh: https://docs.bokeh.org/en/latest/docs/gallery/image.html
HoloViews: https://holoviews.org/reference/elements/bokeh/Image.html
Matplotlib: https://matplotlib.org/stable/tutorials/introductory/images.html
Plotly: https://plotly.com/python/imshow/

Examples

import hvplot.xarray
import xarray as xr

ds = xr.tutorial.open_dataset('air_temperature')
ds.hvplot.image(x='lon', y='lat', z='air', groupby='time', cmap='kbc_r')

Backend-specific styling options#

Bokeh

alpha, cmap, muted, visible

Matplotlib

alpha, clims, cmap, filterrad, interpolation, norm, visible

Examples#

TBD

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