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by Scott D'Angelo, David Taieb | Updated September 17, 2017 - Published July 17, 2017
Built for anyone using data to create Jupyter Notebooks and other artifacts, this pattern shows the power of the open source helper library PixieDust. With PixieDust, hosted on IBM Watson™ Studio, a developer or other user can quickly create charts, graphs, and tables without complex code, in an interactive and dynamic manner. In addition, PixieApps are used to embed UI elements directly in the Jupyter Notebook. Given an open source data provider like the city of San Francisco’s DataSF Open Data, PixieDust and IBM Watson Studio can empower the user to analyze and share data visualizations.
DataSF Open Data provides hundreds of data sets from the city and county of San Francisco. In this pattern, we demonstrate how to incorporate open data into a Jupyter Notebook hosted on IBM Watson Studio, and how to quickly and easily create graphs and charts using PixieDust. We then use PixieApps to create UI elements that can be run directly in the Jupyter Notebook.
When you have completed this pattern, you will understand how to:
Find the detailed steps for this pattern in the README. The steps show you how to:
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