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Datashader is a graphics pipeline system for creating meaningful representations of large amounts of data. It breaks the creation of images into 3 steps:

1. Projection

   Each record is projected into zero or more bins, based on a specified glyph.

2. Aggregation

   Reductions are computed for each bin, compressing the potentially large dataset into a much smaller aggregate.

3. Transformation

   These aggregates are then further processed to create an image.

Using this very general pipeline, many interesting data visualizations can be created in a performant and scalable way. Datashader contains tools for easily creating these pipelines in a composable manner, using only a few lines of code.

The project is under active development, and all the code and documentation is subject to frequent changes.

Datashader is available using the conda package manager, from the bokeh channel:

conda install -c bokeh datashader

Several examples can be found in the examples directory.

The core concepts of datashader are based off the concept of Abstract Rendering:

• Abstract Rendering: Out-of-core Rendering for Information Visualization (SPIE Conference on Visualization and Data Analysis 2014)