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With Holoviews, your data visualizes itself.
The main features of holoviz/holoviews are: Data Visualization.
Projects with overlapping indexed features include: contextlab/hypertools — A Python toolbox for gaining geometric insights into high-dimensional data. has2k1/plotnine — Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative… holoviz/datashader — | | | | --- | --- | | Downloads | | Build Status | | | Coverage | | | Latest dev release | | | Latest release | | |… holoviz/hvplot — A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews. ing-bank/popmon — Monitor the stability of a Pandas or Spark dataframe ⚙︎. bokeh/bokeh — Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance…
A Python toolbox for gaining geometric insights into high-dimensional data
Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative statistical plotting framework and multi-panel plotting engine, allowing users to create complex charts by mapping data variables to visual properties such as position, color, and size. The project is distinguished by its use of a layered composition model and a statistical transformation engine that performs aggregations and computations before rendering visuals. It features a comprehensive system for multi-panel faceting, which enables the splitting of a single visualization into
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Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i