2016 - Bryan Van de Ven - Interactive Data Visualization Applications for the Browser with Bokeh

Description
Bokeh (http://bokeh.pydata.org/en/latest) provides a compelling open-source platform for creating interactive data visualization applications in the browser. This talk will demonstrate Bokeh's newest capabilities: the second generation Bokeh server, APIs for streaming data, new hooks for user-extensibility (e.g. to easily leverage JavaScript 3D plot libraries), new features for GIS, and more.
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Abstract
With support from the DARPA XDATA Initiative, commercial engagements, and contributions from over 150 community members, the Bokeh visualization library (http://bokeh.pydata.org) has grown into a large, successful open source project with heavy interest and following on GitHub (https://github.com/bokeh/bokeh). The principal goals of Bokeh are to provide capability to developers and domain experts: easily create and share interactive, versatile, and powerful visualizations that extract insight from data sets that may be remote, large, or streaming. Bokeh provides a platform for anyone to create interactive data and visualization applications in the browser for themselves, their colleagues, or for a wider audience.

This talk will give a quick overview of recent developments, and demonstrate some of the newest capabilities of Bokeh including:

* Bokeh applications and the second generation Bokeh server (that is more performant, better documented, and much simpler to use and deploy)
* APIs for streaming data (both in the notebook and Bokeh applications)
* The ability to extend Bokeh with your own custom functionality (for example to create 3D plots or network graphs)
* Recent GIS features such as support for GeoJSON and tiled map data sources
* The new Datashader library that can be used together with Bokeh to visualize billions of data points.

Finally the talk will discuss near-term plans for the project, it's governance, and community development.
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Bio:
Bryan studied undergraduate CS and Math at UT Austin, and graduate Physics at UCLA. Currently he leads the technical effort for work done on the Bokeh project at Continuum Analytics. Previously, he has worked on feature detection and classification systems for submarine platforms, automated tools for financial risk modeling, and workflow optimization for fluid mixing simulations. He has also taught Basic, Advanced, and Scientific Python courses to more than 1500 students in the last four years.
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https://youtu.be/xqwCxuEBpxk

Transcript

1. Bryan Van de Ven bryanv@continuum.io @bigreddot PyBay 2016 Data Visualization with Bokeh https://speakerdeck.com/bryanv/pybay-2016-datavis-with-bokeh
2. No JavaScript Bokeh? https://bokeh.pydata.org/en/latest Interactive visualization, widgets, and tools For the browser, with or without a server Versatile and high-level graphics Streaming, dynamic, large data
3. No JavaScript No JavaScript Bokeh? https://bokeh.pydata.org/en/latest Interactive visualization, widgets, and tools For the browser, with or without a server Versatile and high-level graphics Streaming, dynamic, large data
4. Prologue
5. Prologue LOGO: Simple inputs, sophisticated outputs
6. Turtles All The Way Down
7. Turtles All The Way Down Note to self: future Bokeh app example idea
8. Prologue LOGO: Simple inputs, sophisticated outputs
9. Prologue LOGO: Simple inputs, sophisticated outputs Fractint: Making pictures from math
10. Fractals All The Way Down
11. Prologue LOGO: Simple inputs, sophisticated outputs Fractint: Making pictures from math
12. Prologue LOGO: Simple inputs, sophisticated outputs The Web?! mod_python and PIL Fractint: Making pictures from math
13. Prologue LOGO: Simple inputs, sophisticated outputs The Web?! mod_python and PIL VTK: My First OSS Fractint: Making pictures from math
14. Prologue LOGO: Simple inputs, sophisticated outputs The Web?! mod_python and PIL VTK: My First OSS Chaco: Interactive rich-client applications Fractint: Making pictures from math
16. Prologue LOGO: Simple inputs, sophisticated outputs The Web?! mod_python and PIL VTK: My First OSS Chaco: Interactive rich-client applications Fractint: Making pictures from math
17. Prologue LOGO: Simple inputs, sophisticated outputs The Web?! mod_python and PIL VTK: My First OSS Chaco: Interactive rich-client applications Conda: Users pay attention Fractint: Making pictures from math
18. Prologue LOGO: Simple inputs, sophisticated outputs The Web?! mod_python and PIL VTK: My First OSS Chaco: Interactive rich-client applications Conda: Users pay attention Bokeh: All of the above Fractint: Making pictures from math
20. Community Setting the Stage
21. Community Setting the Stage
22. Community Makes the Dream Work Damian Luke Bryan Fabio Mateusz Havoc Almar Peter Maggie Sarah Brendan Kevin
23. Community Makes the Dream Work Damian Luke Bryan Fabio Mateusz Havoc Almar Peter Maggie Sarah Brendan Kevin New faces too: !!!
24. Community Makes the Dream Work Damian Luke Bryan Fabio Mateusz Havoc Almar Peter Maggie Sarah Brendan Kevin Special Thanks: Claire Teng, Dennis Obrien, Julia Signell, Sarah Heim, Tim Snyder, Steven Howell, Andrea Ernlund, Eric Ma, Nikola Hardi, John Dimattio, James Guillochon, Chris Coutinho, and Brigita Sipocz. New faces too: !!!
25. Community Makes the Dream Work Damian Luke Bryan Fabio Mateusz Havoc Almar Peter Maggie Sarah Brendan Kevin Special Thanks: Claire Teng, Dennis Obrien, Julia Signell, Sarah Heim, Tim Snyder, Steven Howell, Andrea Ernlund, Eric Ma, Nikola Hardi, John Dimattio, James Guillochon, Chris Coutinho, and Brigita Sipocz. New faces too: !!!
26. Bokeh Today
27. JavaScript / TypeScript API Today
28. JavaScript / TypeScript API Today http://bokeh.pydata.org/en/latest/docs/user_guide/bokehjs.html
29. Improved Layout Options Today
30. Improved Layout Options Today
31. Simple (to write) Apps for Data Science Today
32. Concentrate on your work Server
33. Concentrate on your work Completely written in Python, no HTML or CSS or “webapp” coding Server
34. Concentrate on your work Completely written in Python, no HTML or CSS or “webapp” coding Server Simple python scripts, no special classes of frameworks
35. Concentrate on your work Completely written in Python, no HTML or CSS or “webapp” coding Server Simple python scripts, no special classes of frameworks Useful for exploratory analysis or sharing and publishing
36. Concentrate on your work Completely written in Python, no HTML or CSS or “webapp” coding Server Simple python scripts, no special classes of frameworks Useful for exploratory analysis or sharing and publishing Automatically mirrors and synchronizes Python and browser state
37. Concentrate on your work Completely written in Python, no HTML or CSS or “webapp” coding Connect the full PyData stack to interactive web apps Server Simple python scripts, no special classes of frameworks Useful for exploratory analysis or sharing and publishing Automatically mirrors and synchronizes Python and browser state
38. Streaming Data Today Two new data source methods: .stream to append data incrementally to column ends .patch for random access updates anywhere
39. Custom Extensions Today http://bokeh.pydata.org/en/latest/docs/user_guide/extensions.html Python class interface JavaScript implementation Normal usage
40. Custom Extensions Today Add capability for…
41. Custom Extensions Today Add capability for… Wrapping different widgets
42. Custom Extensions Today Add capability for… Wrapping different widgets Adapting 3D JavaScript libraries
43. Custom Extensions Today Add capability for… Wrapping different widgets Adapting 3D JavaScript libraries Adding LaTeX labels
44. Custom Extensions Today Add capability for… Wrapping different widgets Adapting 3D JavaScript libraries Adding LaTeX labels Community doesn’t have to wait!
45. Putting It All Together Today
46. (For the Audio Detectives) Today
47. Not just for Python Today http://hafen.github.io/rbokeh Plays well with R ecosystem: HTMLwidget, RMarkdown…
48. Billions and Billions… Today
49. Billions and Billions… Today (of problems plotting large datasets)
50. Billions and Billions… Today Overplotting (of problems plotting large datasets)
51. Billions and Billions… Today Overplotting (of problems plotting large datasets) Saturation
52. Billions and Billions… Today Overplotting (of problems plotting large datasets) Saturation Undersaturation
53. Billions and Billions… Today Overplotting (of problems plotting large datasets) Saturation Undersaturation Binning problems
54. Datashader Today http://datashader.readthedocs.io/en/latest/ Flexible, configurable pipeline for automatic rendering
55. Datashader Today http://datashader.readthedocs.io/en/latest/ Flexible, configurable pipeline for automatic rendering Solves problems of overplotting, underplotting, saturation
56. Datashader Today http://datashader.readthedocs.io/en/latest/ Flexible, configurable pipeline for automatic rendering Solves problems of overplotting, underplotting, saturation Mitigates binning problems by affording interactivity across large datasets
57. Datashader Today http://datashader.readthedocs.io/en/latest/ Flexible, configurable pipeline for automatic rendering Statistical transforms are a first-class aspect of visualization Solves problems of overplotting, underplotting, saturation Mitigates binning problems by affording interactivity across large datasets
58. Datashader Today http://datashader.readthedocs.io/en/latest/ An independent project under the Bokeh GitHub organization Flexible, configurable pipeline for automatic rendering Statistical transforms are a first-class aspect of visualization Solves problems of overplotting, underplotting, saturation Mitigates binning problems by affording interactivity across large datasets
59. Speaking of Dask Today http://dask.pydata.org/en/latest/
60. Speaking of Dask Today http://dask.pydata.org/en/latest/ A pure Python library for parallel and distributed computing
61. Speaking of Dask Today http://dask.pydata.org/en/latest/ A pure Python library for parallel and distributed computing Comes with a Bokeh app for monitoring performance of distributed tasks
62. Speaking of Dask Today http://dask.pydata.org/en/latest/ A pure Python library for parallel and distributed computing Comes with a Bokeh app for monitoring performance of distributed tasks “Invaluable for understanding and optimizing distributed computing performance.”
63. Speaking of Dask Today http://dask.pydata.org/en/latest/ A pure Python library for parallel and distributed computing Comes with a Bokeh app for monitoring performance of distributed tasks “Invaluable for understanding and optimizing distributed computing performance.” “It's not something for which I need to go out and find a web developer to help me with.”
64. To be continued…
65. • Arbitrary computed columns (e.g. color) To be continued…
66. • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) To be continued…
67. • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship To be continued…
68. • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! To be continued…
69. Tomorrow Better Late Than Never
70. To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars!
71. To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! • Community repo for extensions
72. To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! • Community repo for extensions • Bokeh “develop” mode
73. Tomorrow Bokeh Authoring https://www.youtube.com/watch?v=VOAXC7XUCto
74. Tomorrow Bokeh Authoring https://www.youtube.com/watch?v=VOAXC7XUCto
75. To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! • Community repo for extensions • Bokeh “develop” mode
76. • Binary protocol for arrays To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! • Community repo for extensions • Bokeh “develop” mode
77. • Binary protocol for arrays • JupyterLab integration To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! • Community repo for extensions • Bokeh “develop” mode
78. • Binary protocol for arrays • JupyterLab integration • 1.0 To be continued…
 (continued) • Arbitrary computed columns (e.g. color) • SVG output (Chrome Headless) • NumFOCUS fiscal sponsorship • Colorbars! • Community repo for extensions • Bokeh “develop” mode
79. Resources • GitHub: https://github.com/Bokeh/bokeh • Documentation: http://bokeh.pydata.org/en/latest • Example Apps: https://demo.bokehplots.com • Tutorials: http://nbviewer.jupyter.org/github/bokeh/bokeh-notebooks/blob/master/index.ipynb • Mailing List: https://groups.google.com/a/continuum.io/forum/#!forum/bokeh • Gitter Chat: https://gitter.im/bokeh/bokeh
80. Call to Action Install Bokeh and provide feedback • BSD license for everything (JS, Python, server) • https://github.com/Bokeh/bokeh
81. Call to Action Install Bokeh and provide feedback • BSD license for everything (JS, Python, server) • https://github.com/Bokeh/bokeh Engage us to work on custom apps and dashboards • Code integration, analytical and visualization expertise • Feedback helps the open source efforts