Widgets

Jupyter notebooks can also include interactive elements, referred to as widgets as in Lesson 2, like buttons, text input fields, sliders, and other GUI elements, as well as visualizations, plots, and animations. Figure 3.12 shows an example that places three button widgets and then simply prints out which button has been pressed when you click on them. The ipywidgets and IPython.display packages imported at the beginning are the main packages required to place the widgets in the notebook. We then define a function that will be invoked whenever one of the buttons is clicked. It simply prints out the description attribute of the button (b.description). In the for-loop we create the three buttons and register the onButtonClick function as the on_click event handler function for all of them.

from ipywidgets import widgets
from IPython.display import display

def onButtonClick(b):
    print("Button " + b.description + " has been clicked")
	for i in range(1,4):
        button = widgets.Button(description=str(i))

display(button)
button.on_click(onButtonClick)

Figure 3.12 Notebook example using three button widgets and an event handler function that prints out which button has been clicked

Note- the following might not apply to Notebooks in Pro, but it is good information to know if and when using the stand alone Jupyter Notebook session. Doing this outside of Pro’s Package Manager might corrupt your environment so be sur to perform this on a dedicated env clone.

If you get an error with this code "Failed to display Jupyter Widget of type Button" that means the widgets are probably not installed which we can potentially fix in our Anaconda prompt:

conda install -n base -c conda-forge widgetsnbextension
conda install -n AC37 -c conda-forge ipywidgets

After installing the packages, exit your Jupyter notebook and restart it and try to re-run your code. It is possible you will receive the error again as the widget tries to run before the Javascript library that runs the widgets has opened. In that case try to select your code, wait a few more seconds and then click Run.

If you are still getting an error, it is likely that your packages did not install properly (or in a way that Jupyter/Anaconda could find them). The fix for this is to close Jupyter Notebook, return to Anaconda Navigator, click Environments (on the left), choose your environment and then search for "ipy", you may need to either change the "Installed" dropdown to "Not Installed" if they are missing or perhaps they should be updated (by clicking on the upward point arrow or the blue text).

Figure 3.13 Anaconda Navigator showing how to install / update packages

It is easy to imagine how this example could be extended to provide some choices on how the next analysis step in a longer Data Science project should be performed. Similarly, a slider or text input field could be used to allow the notebook user to change the values of important input variables.

Lesson content developed by Jan Wallgrun and James O’Brien