FAQ ¶

Can I use HoloViews without IPython/Jupyter? ¶

Yes! The IPython/Jupyter notebook support makes a lot of tasks easier, and helps keep your data objects separate from the customization options, but everything available in IPython can also be done directly from Python. For instance, since HoloViews 1.3.0 you can render an object directly to disk, with custom options, like this:

import holoviews as hv
renderer = hv.renderer('matplotlib').instance(fig='svg', holomap='gif')
renderer.save(my_object, 'example_I', style=dict(Image={'cmap':'jet'}))

This process is described in detail in the Customizing Plots user guide. Of course, notebook-specific functionality like capturing the data in notebook cells or saving cleared notebooks is only for IPython/Jupyter.

How should I use HoloViews as a short qualified import? ¶

We recommend importing HoloViews using import holoviews as hv .

Why does my output look different from what is shown on the website? ¶

HoloViews is organized as data structures that have corresponding plotting code implemented in different plotting-library backends, and each library will have differences in behavior. Moreover, the same library can give different results depending on its own internal options and versions. For instance, Matplotlib supports a variety of internal plotting backends, and these can have inconsistent output. HoloViews will not switch Matplotlib backends for you, but when using Matplotlib we strongly recommend selecting the ‘agg’ backend for consistency:

from matplotlib import pyplot
pyplot.switch_backend('agg')

You can generally set options explicitly to make the output more consistent across HoloViews backends, but in general HoloViews tries to use each backend’s defaults where possible.

How do I index into my object? ¶

In any Python session, you can look at print(obj) . For an explanation of how this information helps you index into your object, see our Composing Elements user guide.

How do I find out the options for customizing the appearance of my object? ¶

If you are in the IPython/Jupyter Notebook you can use the cell magic %%output info=True at the top of your code cell. This will present the available style and plotting options for that object.

The same information is also available in any Python session using hv.help(obj) . For more information on customizing the display of an object, see our Customizing Plots user guide.