Bryan Van de Ven

Bryan has worked for Anaconda (formerly Continuum Analytics) for six and half years. During that time he has taught dozens of Python training courses at various levels, and has spoken at many conferences. However, for the majority of that time, he has managed the open source project Bokeh (https://bokeh.pydata.org/en/latest/index.html), which affords sophisticated interactive data visualization in the browser directly from Python. The Bokeh project started in late 2012 and since then has grown to a large community of several hundred thousand users and over 300 all-time contributors.

Prior to working at Anaconda, Bryan spent a brief period flirting with mobile development. Before that, he worked on sonar systems for submarine vehicles.

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Practice Best Practice with Bokeh

AI & Data, Novice
8/16/2018 | 9:15 AM-12:45 PM | Microsoft Reactor

Description

Interested in creating interactive data visualizations in the browser from Python? Learn about the latest with Bokeh 1.0 and the best practices from their core developer.

Abstract

Bokeh is a popular data visualization tool used in a wide variety of disciplines such as:

  • Finance data analysis
  • Finance, management, big data mining
  • EDA, Dashboards
  • Graphing business patterns (sadly private to my employer)
  • Web applications for weather data and renewable energy forecasts
  • Data mining visualisation
  • Viewing energy production data
  • Disaster resource management (in dev), training, data exploration
  • Interactive Dashboards for different areas in our Company
  • Displaying agricultural sensor data online
  • Mapping clinical trials using AERO plot https://www.portalresearch.org/aero-graph.html

With a Bokeh 1.0 release in mid-2018, this workshop aims to provide a new definitive resource for effective use of Bokeh. We will cover topics such as:

  • Brief Overview of Bokeh architecture and concepts
  • Knobs and Dials, how to control how things look and how to use the ref guide
  • Adding Interactions, including custom JS code
  • Handling Categorical Data in different ways
  • Embedding and Exporting standalone Bokeh documents
  • Bokeh Server Applications (in the notebook and in dashboard templates)
  • Extending Bokeh (advanced, time permitting)

Who should attend?

Those interested in creating interactive data visualizations in the browser from Python using the latest best practices in Bokeh, and those interested in hearing about what's up with Bokeh 1.0.

Getting ready

  • Students should bring a laptop and be prepared to write code and work through tutorial material.
  • Installed the latest Anaconda, then run "conda update bokeh" to obtain the latest version of Bokeh. However, "pip install bokeh" will also work for non-Anaconda users.
  • Have Pandas and Jupyter notebook installed