User Guide ¶
The User Guide is the primary resource documenting key concepts that will help you use HoloViews in your work. For newcomers, a gentle introduction to HoloViews can be found in our Getting Started guide and an overview of some interesting HoloViews examples can be found in our Gallery . If you are looking for a specific component (or wish to view the available range of primitives), see our Reference Gallery .
Core guides ¶
These user guides provide detailed explanation of some of the core concepts in HoloViews:
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- Annotating your Data
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Core concepts when annotating your data with semantic metadata.
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- Composing Elements
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Composing your data into layouts and overlays with the
+and*operators.
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- Customizing Plots
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Controlling the look and feel of the visual representation.
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- Dimensioned Containers
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Multi-dimensional containers for animating and faceting your data flexibly.
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- Building Composite Objects
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How to build and work with nested composite objects.
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- Live Data
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Lazily generate data on the fly and generate engaging interactive visualizations.
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- Gridded Datasets
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Explore gridded data (n-dimensional arrays) with NumPy and XArray .
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- Indexing and Selecting Data
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Select and index subsets of your data with HoloViews.
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- Transforming Elements
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Apply operations to your data that can be used to build data analysis pipelines
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- Responding to Events
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Allow your visualizations to respond to Python events using the ‘streams’ system.
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- Custom Interactivity
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Use Bokeh and ‘linked streams’ to directly interact with your visualizations.
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- Data Processing Pipelines
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Chain operations to build sophisticated, interactive and lazy data analysis pipelines.
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- Working with large data
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Leverage datashader to interactively explore billions of datapoints.
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- Creating interactive dashboards
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Use external widget libraries to build custom, interactive dashboards.
Supplementary guides ¶
These guides provide detail about specific additional features in HoloViews:
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- Installing and Configuring HoloViews
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Additional information about installation and configuration options.
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- Plotting with Bokeh
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Styling options and unique Bokeh features such as plot tools and using bokeh models directly.
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- Deploying Bokeh Apps
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Using bokeh server using scripts and notebooks.
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- Plotting with matplotlib
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Styling options and unique Matplotlib features such as GIF/MP4 support.
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- Plotting with plotly
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Styling options and unique plotly features, focusing on 3D plotting.
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- Working with renderers and plots
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Using the
RendererandPlotclasses for access to the plotting machinery.
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- Exporting and Archiving
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Archive both your data and visualization in scripts and notebooks.
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- Continuous Coordinates
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How continuous coordinates are handled, specifically focusing on
ImageandRastertypes.