Tips and Tutorials \ HoloViz Tutorial
Learn how to visualize and explore data efficiently using HoloViz tools, compatible with various Python data types and libraries.
Type: Gallery
Categories: Visualization Tools, Python Stack
Motivation
HoloViz provides a suite of tools for visualizing large, complex datasets in Python, making it easier for users to build powerful, interactive plots and dashboards. It supports a wide range of standard Python data types, such as Pandas and Dask DataFrames, NumPy and Xarray arrays, and even remote data through the Intake data catalog.
This tutorial will introduce you to HoloViz, its core tools, and how to get started with creating stunning visualizations using your local or remote data.
Prerequisites
- Basic knowledge of Python and data analysis.
- Experience with Pandas, Dask, or NumPy will be helpful but not mandatory.
- HoloViz installed. You can find the instructions on the HoloViz website.
Tutorial Content
HoloViz tools and examples work with standard Python data types (lists, dictionaries, etc.), plus Pandas or Dask DataFrames, NumPy, Xarray, or Dask arrays, including remote data from the Intake data catalog. It also uses Dask and Numba to speed up computations and supports both GPUs and CPUs to utilize all available hardware resources.
To see the tool in action and explore more, check out the following tutorials:
How to Contribute
You can contribute by creating new notebooks or improving existing ones. Fork the repository, make your changes, and submit a pull request. Contributions are always welcome!
For further questions or support, visit the HoloViz community forum or contact HoloViz Support.
See Also
Contacts
Questions ? Get help on the Forum