Chapter 2. Python and Jupyter Notebooks to Power your Data Analysis

"The Best Line of Code is the One You Didn't Have to Write!"

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In the previous chapter, I gave a developer's perspective on data science based on real experience and discussed three strategic pillars required for successful deployment with in the enterprise: data, services, and tools. I also discussed the idea that data science is not only the sole purview of data scientists, but rather a team sport with a special role for developers.

In this chapter, I'll introduce a solution—based on Jupyter Notebooks, Python, and the PixieDust open source library—that focuses on three simple goals:

  • Democratizing data science by lowering the barrier to entry for non-data scientists
  • Increasing ...

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