The Rise of Data Science Notebooks

(Sudowoodo/Shutterstock) Interactive notebooks are experiencing a rise in popularity. How do we know? They’re replacing PowerPoint in presentations, shared around organizations, and they’re even taking workload away from BI suites (more on that later). Even though they’ve become prominent in the past few years, they have a long history. First notebooks were available in packages like Mathematica and Matlab, used primarily in academia. More recently they’ve started getting traction in Python community with iPython Notebook. Today there are many notebooks to choose from: Jupyter (successor to the iPython Notebook), R Markdown, Apache Zeppelin, Spark Notebook, Databricks Cloud, and more. There are kernels/backends to multiple languages, such as Python, Julia, Scala, SQL, and others. Traditionally, notebooks have been used to document research and make results reproducible, simply by rerunning the notebook…


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