Jupyter provides the ability to use a variety of languages when developing a Notebook. Each of the languages is supported through the use of an engine that provides all of the programmatic interface from the coded language instruction that you write with the underlying Notebook. Several of the popular languages in use are Python, R, Julia, JavaScript, and Scala. In this chapter, we will show you the steps to add these engines to your Jupyter installation so that you can script your Notebook in the language you like.
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Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
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Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
Read more about Dan Toomey