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#Install ipython console for free
✅ Updated regularly for free (latest update in April 2021) ✅ 30-day no-question money-back guarantee This function call is situated before the Matplotlib import: Here, we've told the Jupyter notebook to use Qt to generate the frame on our local machine instead. Let's start off with trying to plot on an external window from the notebook: %matplotlib qt Matplotlib Plot On External Window using IPython/Jupyter Jupyter automatically sets a Matplotlib backend, though, this can be overriden using magic functions, which are called with the % character. However, you can also display the plot outside of the notebook, which can be done by changing the Matplotlib backend. These plots are by default, displayed inline, which means, they're displayed in the notebook itself. With Jupyter notebooks, this isn't necessary as the plots are displayed after running the cells containing the code that generates them. Usually, displaying plots involves using the show() function from PyPlot.
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If you would like the visualizations themselves to be included in the notebook body, you make use of the inline command, which refers to a Matplotlib backend. However, if you shared this notebook with someone in its current form - they'd have to run the code themselves to see the visualizations. This is how you'd usually visualize data in a Jupyter notebook.