Jupyter Widget Sparkline encapsulates jQuery Sparklines as a jupyter notebook widget.
The following example creates a simple Sparkline barchart widget:
from jupyter_widget_sparkline import Sparkline
sparkline = Sparkline()
sparkline.data = { 'values': [10,8,5,7,4,4,1], 'type':'bar'}
display(sparkline)Options and values are passed throught the data field.
See the documentation of the jQuery Sparklines for all the options.
The region field is updated when users click on the content of a sparkline, as shown in the example:
sparkline2 = Sparkline()
output2 = widgets.Output()
def region_changed2(change):
with output2:
output2.clear_output()
print(change['new'])
sparkline2.data = { 'values': [10,8,5,7,4,4,1], 'type':'bar'}
sparkline2.observe(region_changed2, names='region')
widgets.VBox([sparkline2, output2])The widget is dynamic so when the data field is changed, the widget is updated.
To install use pip:
$ pip install jupyter_widget_sparkline
$ jupyter nbextension enable --py --sys-prefix jupyter_widget_sparkline
To install for jupyterlab
$ jupyter labextension install jupyter_widget_sparkline
For a development installation (requires npm),
$ git clone https://github.com/Inria/jupyter-widget-sparkline.git
$ cd jupyter-widget-sparkline
$ pip install -e .
$ jupyter nbextension install --py --symlink --sys-prefix jupyter_widget_sparkline
$ jupyter nbextension enable --py --sys-prefix jupyter_widget_sparkline
$ jupyter labextension install js
When actively developing your extension, build Jupyter Lab with the command:
$ jupyter lab --watch
This takes a minute or so to get started, but then automatically rebuilds JupyterLab when your javascript changes.
Note on first jupyter lab --watch, you may need to touch a file to get Jupyter Lab to open.