About Jupyter Notebook

Note: This help file does not attempt to document the entire Jupyter Notebook experience or cover how to use the programming languages it supports. We recommend the following resource for additional information on these different components: https://nbviewer.jupyter.org/github/ipython/ipython/blob/3.x/examples/Notebook/Index.ipynb

Once you've completed your research and curated your results list / document set, you can import the dataset into the Jupyter Notebook workspace (which is integrated into the Nexis® Data Lab platform). You can then select one or more prepackaged Python or R notebook libraries and begin your analysis of the dataset. You can modify your copy of the prepackaged libraries or copy and paste your own code into the notebook.

The Jupyter Notebook helps you create and share documents that contain live code, equations, visualizations, and narrative text. Because the Notebook environment is part of Nexis Data Lab, the application provides a seamless transition between your research and your analysis.

Once your analysis is finished, you can download your findings, visualizations, and code used to develop your analysis. Since the LexisNexis full-text data used during your analysis stays in the workspace, you can easily recreate your analysis by signing back in to Nexis Data Lab and activating the saved workspace from the home page. From there, you can copy your Python or R library back into the notebook and rerun your analysis.