Analyze traffic data from the city of San Francisco  

Create charts, graphs, and maps using open city datasets

Last updated | By Scott D’Angelo, David Taieb

Description

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 Data Science Experience (DSX), 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’s DSX can empower the user to analyze and share data visualizations.

Overview

DataSF Open Data provides hundreds of data sets from the city and county of San Francisco. In this journey, we demonstrate how to incorporate open data into a Jupyter Notebook hosted on IBM Data Science Experience (DSX), 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:

Flow

  1. Load the provided notebook onto the IBM Data Science Experience platform.
  2. DataSF Open Data traffic info is loaded into the Jupyter Notebook.
  3. The notebook analyzes the traffic info.
  4. You can interactively change charts and graphs.
  5. A PixieApp dashboard is created and can be interacted with.

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