An [extension](https://github.com/dask/dask-labextension) to manage Dask clusters, as well as embed Dask's dashboard plots directly into JupyterLab panes.
Watch [this](https://www.youtube.com/watch?feature=player_embedded&v=EX_voquHdk0) video until the end to unterstand how to use Dask in JupyterLab. At the moment we only offer to use the panels inside of JupyterLab.
We have introduction notebooks for this extensions [here](https://gitlab.version.fz-juelich.de/jupyter4jsc/j4j_notebooks/tree/master/001-Extensions)(or open the gitlab extension on the left sidebar).
A [Table of Contents extension](https://github.com/jupyterlab/jupyterlab-toc) for JupyterLab. This auto-generates a table of contents in the left area when you have a notebook or markdown document open.
The entries are clickable, and scroll the document to the heading in question.
[Voilà](https://github.com/voila-dashboards/voila) turns Jupyter notebooks into standalone web applications.
Unlike the usual HTML-converted notebooks, each user connecting to the Voilà tornado application gets a dedicated Jupyter kernel which can execute the callbacks to changes in Jupyter interactive widgets.
This extension allows you to render a Notebook with Voilà, so you can see how your Notebook will look with it.
You can download a test notebook with the following command:
[Quick Open](https://github.com/parente/jupyterlab-quickopen) allows you to quickly open a file in JupyterLab by typing part of its name. Just click on the lens symbol at the left sidebar.
<spanstyle="color:darkorange">Takes a long time on HPC systems.</span>
Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.
Please read the [documentation](https://plotly.com/python).