Pycon Israel 2021

Tutorial: Using Python HoloViz Technologies to Create Interactive Presentations
05-02, 16:00–16:45 (Asia/Jerusalem), PyData Track 1

The tutorial will introduce two interactive plots libraries: HoloViews, and panel and show how those can be used to create static html files with interactive graphics


The HoloViz project provides a set of Python libraries for high-level visualization of complex datasets. They are particularly useful for handling big data and multi-dimensional data that is common in machine-learning applications.
HoloViz technologies support multiple graphical engine backends and integrate seamlessly with flexible development and deployment environments like Jupyter notebooks and modern web browsers. The visualization outputs are interactive, with features such as widgets like sliders or selection boxes or hover tools to inspect data, while not requiring any JavaScript, HTML, CSS, or other web-technology expertise.
This tutorial will focus on two HoloViz libraries:

HoloViews: high level interface providing plots (heat maps, histograms, spikes, etc.) in many spatial and temporal combinations, with or without widgets for selecting along dimensions
Panel: simple application and dashboard creation from images, plots, Markdown, LaTeX, and other elements into one HTML page incorporating interactive tabs and widgets.

During the tutorial an interactive presentation will be constructed to show the attendees how to construct their own interactive poster / presentation.
Sample References:
• HoloViz web site: https://holoviz.org
• HoloViz on Github: https://github.com/holoviz/holoviz
• Jacob Barhak, Joshua Schertz, Visualizing Machine Learning of Units of Measure using PyViz, PyData Austin 2019, 6-7 December 2019, Galvanize Austin. Presentation: https://jacob-barhak.github.io/Presentation_PyData_Austin_2019.html Video: https://youtu.be/KS-sRpUvnD0


Session language

English

Target audience

Developers, Users, Data Scientists

Jacob Barhak is a Computational Disease Modeler focusing on machine comprehension of clinical data. The Reference Model for disease progression that is the most validated Diabetes model known worldwide and also applied to model COVID-19 was self developed by Dr. Barhak as an independent researcher. His efforts include standardizing clinical data through ClinicalUnitMapping.com. He is the developer of the Micro Simulation Tool (MIST). Dr. Barhak has diverse international background in engineering and computing science. He is active within the python community and runs the Austin Evening of Python Coding meetup. For additional information please visit http://sites.google.com/site/jacobbarhak/

Jim Bednar is the Director of Technical Consulting at Anaconda, Inc. Dr. Bednar holds a Ph.D. in Computer Science from the University of Texas, along with degrees in Electrical Engineering and Philosophy. He has published more than 50 papers and books about the visual system and about software development. Dr. Bednar manages the open source Python projects HoloViz, Panel, hvPlot, Datashader, HoloViews, GeoViews, Param, and Colorcet. Before Anaconda, Dr. Bednar was a lecturer and researcher in Computational Neuroscience at the University of Edinburgh, Scotland, as well as a software and hardware engineer at National Instruments.