Brought to you by NumFOCUS Foundation and O’Reilly Media
The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

Schedule: Data visualization sessions

9:00am–12:30pm Wednesday, August 22, 2018
Location: Gramercy A Level: Intermediate
Noemi Derzsy (AT&T Labs)
Networks, also known as graphs, are one of the most crucial data structures in our increasingly intertwined world. Social friendship networks, the web, financial systems, and infrastructure are all network structures. Noemi Derzsy explains how to generate, manipulate, analyze, and visualize graph structures that will help you gain insight about relationships between elements in your data. Read more.
1:30pm–5:00pm Wednesday, August 22, 2018
Location: Murray Hill B
Bruno Goncalves (Data For Science), Matt Brems (General Assembly)
This two-part tutorial presents a sequence of advanced topics in Data Science, based on using Jupyter. Read more.
11:05am–11:45am Thursday, August 23, 2018
Location: Sutton Center/Sutton South Level: Intermediate
Sylvain Corlay (QuantStack), Johan Mabille (QuantStack), Wolf Vollprecht (QuantStack), Martin Renou
Average rating: ****.
(4.67, 3 ratings)
Sylvain Corlay, Johan Mabille, Wolf Vollprecht, and Martin Renou share the latest features of the C++ Jupyter kernel, including live help, auto-completion, rich MIME type rendering, and interactive widgets. Join in to explore one of the most feature-full implementations of the Jupyter kernel protocol that also brings Jupyter closer to the metal. Read more.
11:55am–12:35pm Thursday, August 23, 2018
Location: Nassau Level: Beginner
Chris Harris (Kitware)
Average rating: *****
(5.00, 1 rating)
In silico prediction of chemical properties has seen vast improvements in both veracity and volume of data but is currently hamstrung by a lack of transparent, reproducible workflows coupled with environments for visualization and analysis. Chris Harris offers an overview of a platform that uses Jupyter notebooks to enable an end-to-end workflow from simulation setup to visualizing the results. Read more.
4:10pm–4:50pm Thursday, August 23, 2018
Location: Nassau Level: Intermediate
Nicolas Fernandez (Icahn School of Medicine at Mount Sinai)
Nicolas Fernandez offers an overview of Clustergrammer-Widget, an interactive heatmap Jupyter widget that enables users to easily explore high-dimensional data within a Jupyter notebook and share their interactive visualizations using nbviewer. Read more.
5:00pm–5:40pm Thursday, August 23, 2018
Location: Sutton Center/Sutton South Level: Intermediate
M Pacer (Netflix)
Average rating: ****.
(4.50, 4 ratings)
Jupyter displays a rich array of media types out of the box. M Pacer explains how to use these capabilities to their full potential, covering how to add rich displays to existing and new Python classes and how to customize the way notebooks are converted to other formats. These skills will enable anyone to make beautiful objects with Jupyter. Read more.
11:05am–11:45am Friday, August 24, 2018
Location: Murray Hill Level: Intermediate
Average rating: ****.
(4.00, 1 rating)
Kerim Kalafala and Nicholai L'Esperance share their experiences using Jupyter notebooks as a critical aid in designing the next generation of IBM Power and Z processors, focusing on analytics on graphs consisting of hundreds of millions of nodes. Along the way, Kerim and Nicholai explain how they leverage Jupyter notebooks as part of their overall design system. Read more.
1:50pm–2:30pm Friday, August 24, 2018
Location: Murray Hill Level: Beginner
Seth Lawler (Dewberry)
Average rating: *****
(5.00, 1 rating)
Creating flood maps for coastal and riverine communities requires geospatial processing, statistical analysis, finite element modeling, and a team of specialists working together. Seth Lawler explains how using the feature-rich JupyterLab to develop tools, share code with team members, and document workflows used in the creation of flood maps improves productivity and reproducibility. Read more.
1:50pm–2:30pm Friday, August 24, 2018
Location: Nassau Level: Intermediate
David Koop (University of Massachusetts Dartmouth)
Average rating: ****.
(4.50, 2 ratings)
Dataflow notebooks build on the Jupyter Notebook environment by adding constructs to make dependencies between cells explicit and clear. David Koop offers an overview of the Dataflow kernel, shows how it can be used to robustly link cells as a notebook is developed, and demonstrates how that notebook can be reused and extended without impacting its reproducibility. Read more.
1:50pm–2:30pm Friday, August 24, 2018
Location: Concourse A: Business Summit Level: Beginner
George Williams (GSI Technology), Harini Kannan (Capsule8), Alex Comerford (Capsule8)
Average rating: ****.
(4.50, 2 ratings)
The key to successful threat detection in cybersecurity is fast response. George Williams, Harini Kannan, and Alex Comerford offer an overview of specialized extensions they have built for data scientists working in cybersecurity that can be used and deployed via JupyterHub. Read more.
4:10pm–4:50pm Friday, August 24, 2018
Location: Nassau Level: Beginner
Lindsay Richman (McKinsey & Co.)
Average rating: ****.
(4.50, 2 ratings)
JupyterLab and Plotly both provide a rich set of tools for working with data. When combined, they create a powerful computational environment that enables users to produce versatile, robust visualizations in a fast-paced setting. Lindsay Richman demonstrates how to use JupyterLab, Plotly, and Plotly's Python-based Dash framework to create dynamic charts and interactive reports. Read more.