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Plotting in Jupyter notebooks is an easy and powerful way to visualise data and interact with the visualisations. Below we show a simple plotting example:

Note the “%matplotlib inline” line in the above code. This will produce an in‐line plot within the notebook, as follows:

But Jupyter also provides tools for creating interactive plots. This can be achieved by replacing the “%matplotlib inline” instruction to “%matplotlib notebook,” producing a plot as follows:

This interactive plot allows the user to easily pan, zoom, and download the plot.