As you may already know, 2018 was a pivotal year for CEBIT for many reasons. The fair has undergone a complete makeover; you would hardly recognize it. After almost 50 years, the expo not only changed its name by capitalising every letter (CeBIT has transformed to become CEBIT), it also changed its scheduling, opting for...
Built for anyone using data to create Jupyter Notebooks and other artifacts, this journey 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 journey, you will understand how to:
- Load the provided notebook onto the IBM Watson Studio platform.
- DataSF Open Data traffic info is loaded into the Jupyter Notebook.
- The notebook analyzes the traffic info.
- You can interactively change charts and graphs.
- A PixieApp dashboard is created and can be interacted with.