Datashader: Plotting all your data
Dr. James A. Bednar, Director of Technical Consulting at Anaconda, Inc., joins Coiled to discuss Datashader.
Dr. James A. Bednar, who works at Anaconda running consulting projects and maintaining the HoloViz suite of open-source tools, joins Coiled to discuss Datashader.
Datashader renders even the largest datasets quickly and accurately, helping reveal their true distribution.
Without Datashader, additional data points often obscure rather than reveal your data, with each new point overplotting and hiding previous ones. Datashader numerically aggregates all the data points falling in each pixel, then uses nonlinear colormapping to visualize both trends and outliers faithfully.
Datashader’s computation is accelerated on CPUs using Numba (+ RAPIDS on GPUs) and distributed using Dask so that you can make full use of all available hardware. To help you see patterns at every spatial scale, Datashader has been integrated with Bokeh and Plotly (via HoloViews) and with Matplotlib, providing interactive plotting for billions of points even on an ordinary laptop.
After attending, you’ll know:
What sort of plotting issues Datashader helps you avoid
How to apply Datashader to your Pandas or Xarray data
When to use Dask with Datashader
More on Dr. Bednar:
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, Lumen, and Colorcet. Before Anaconda, Dr. Bednar was a lecturer and researcher in Computational Neuroscience at the University of Edinburgh from 2004-2015, and before that a hardware engineer working on data acquisition at National Instruments.