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
-
Core concepts when annotating your data with semantic metadata.
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- Composing Elements
-
Composing your data into layouts and overlays with the
+
and*
operators.
-
- Customizing Plots
-
Controlling the look and feel of the visual representation.
-
- Dimensioned Containers
-
Multi-dimensional containers for animating and faceting your data flexibly.
-
- Building Composite Objects
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How to build and work with nested composite objects.
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- Live Data
-
Lazily generate data on the fly and generate engaging interactive visualizations.
-
- Gridded Datasets
-
Explore gridded data (n-dimensional arrays) with NumPy and XArray .
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- Indexing and Selecting Data
-
Select and index subsets of your data with HoloViews.
-
- Transforming Elements
-
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.
-
- Custom Interactivity
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Use Bokeh and ‘linked streams’ to directly interact with your visualizations.
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- Data Processing Pipelines
-
Chain operations to build sophisticated, interactive and lazy data analysis pipelines.
-
- Working with large data
-
Leverage datashader to interactively explore billions of datapoints.
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- Creating interactive dashboards
-
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.
-
- Plotting with plotly
-
Styling options and unique plotly features, focusing on 3D plotting.
-
- Working with renderers and plots
-
Using the
Renderer
andPlot
classes for access to the plotting machinery.
-
- Exporting and Archiving
-
Archive both your data and visualization in scripts and notebooks.
-
- Continuous Coordinates
-
How continuous coordinates are handled, specifically focusing on
Image
andRaster
types.