Datashader is an open source library for rasterizing large amounts of data into attractive, accurate images. It automates the process of creating meaningful representations of large amounts of data.
Datashader breaks the creation of images into a series of explicit steps that allow computations to be done on intermediate representations. This approach allows accurate and effective visualizations to be produced automatically, and also makes it simple for data scientists to focus on particular data and relationships of interest in a principled way.
Datashader is designed for working with large datasets, for cases where it is essential to faithfully represent the distribution of your data. It generates a fixed-size data structure (regardless of the original number of records) that gets transferred to your local browser for display.
Key Features
- Fast server-side engine designed for dynamic data aggregation.
- Handles interactive visualizations of really large data sets including sets with billions of rows.
- It aggregates data and sends pixels instead of sending data to the client.
- A compute layers that works with Bokeh.
- Provides a flexible series of processing stages that map from raw data into viewable images.
- Projection – each record is projected into zero or more bins of a nominal plotting grid shape, based on a specified glyph.
- Aggregation – reductions are computed for each bin, compressing the potentially large dataset into a much smaller aggregate array.
- Transformation – these aggregates are then further processed, eventually creating an image.
- Supports both Pandas and Dask data frames for Points, Lines, and Graphs, and xarray arrays for Raster data.
- Provides Point, Line, and Raster glyphs, specified at the canvas/scene level.
- Directly supported by HoloViews, with interactive exploration supported for its Bokeh extension, and static plots supported for its Matplotlib extension.
Website: datashader.org
Support: FAQ, User Guide, GitHub Code Repository
Developer: Continuum Analytics, Inc. and contributors
License: BSD License
Datashader is written in Python. Learn Python with our recommended free books and free tutorials.
Related Software
| Python Visualization Packages | |
|---|---|
| matplotlib | Python 2D plotting library which produces publication quality figures |
| Diagrams | Draw the cloud system architecture in Python code |
| Bokeh | Elegant, concise construction of versatile graphics |
| Dash | Python framework for building analytical web applications |
| seaborn | Python visualization library based on matplotlib |
| Plotly | Interactive, browser-based graphing library for Python |
| VisPy | Visualize massive datasets in real time |
| Vega-Altair | Declarative Visualization in Python |
| plotnine | Grammar of graphics for Python |
| PyQtGraph | Python graphics and GUI library built on PyQt4 / PySide and numpy |
| bqplot | Interactive Plotting Framework for the Jupyter Notebook |
| Vaex | Fast visualization of big data |
| PyVista | 3D plotting and mesh analysis |
| folium | Visualize data in a Leaflet map |
| HoloViews | Make Data Analysis and Visualization Seamless |
| Datashader | Generates aggregate arrays and representations of them as images |
| yt | Multi-code Toolkit for Analyzing and Visualizing Volumetric Data |
| Glumpy | Intuitive interface between NumPy and modern OpenGL |
| GeoViews | Explore and visualize geographical, meteorological, and oceanographic datasets |
| Pygal | Dynamic SVG charting library |
| Glue | Multi-dimensional linked-data exploration |
Read our verdict in the software roundup.
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