Installing HoloViews

The quickest and easiest way to get the latest version of all the recommended packages for working with HoloViews on Linux, Windows, or Mac systems is via the conda command provided by the Anaconda or Miniconda scientific Python distributions:

conda install -c ioam holoviews bokeh

This recommended installation includes the default Matplotlib plotting library backend, the more interactive Bokeh plotting library backend, and the Jupyter/IPython Notebook .

A similar set of packages can be installed using pip , if that command is available on your system:

pip install 'holoviews[recommended]'

pip also supports other installation options, including a minimal install of only the packages necessary to generate and manipulate HoloViews objects without visualization:

pip install holoviews

This minimal install includes only the two required libraries Param and Numpy , neither of which has any required dependencies, which makes it very easy to integrate HoloViews into your workflow or as part of another project.

Alternatively, you can ask pip to install a larger set of packages that provide additional functionality in HoloViews:

pip install 'holoviews[extras]'

This option installs all the required and recommended packages, plus the optional mpld3 , pandas and Seaborn libraries.

Lastly, to get everything , including cyordereddict to enable optional speed optimizations and nose for running unit tests, you can use:

pip install 'holoviews[all]'

Between releases, development snapshots are made available on conda and can be installed using:

conda install -c ioam/label/dev holoviews

To get the very latest development version you can clone our git repositories:

git clone git://github.com/ioam/param.git
git clone git://github.com/ioam/holoviews.git

Once you’ve installed HoloViews, you can get started by launching Jupyter Notebook:

jupyter notebook

Now you can download the tutorial notebooks . unzip them somewhere Jupyter Notebook can find them, and then open the Homepage.ipynb tutorial or any of the others in the Notebook. Enjoy exploring your data!