<![CDATA[holoviz 相关包梳理]]>

<![CDATA[holoviz 相关包梳理]]>单细胞开发中　图表渲染涉及holoviz中的几个关键包　梳理如下：
1.Holoviz包括的包

Holoviz的目标是整合已有工具　对图表开发进行简化
a set of open-source Python packages to streamline the entire process of working with small and large datasets (from a few datapoints to billions or more) in a web browser, whether doing exploratory analysis, making simple widget-based tools, or building multipage standalone dashboards. Building on existing plotting libraries like Bokeh, Matplotlib, and Plotly, the HoloViz ecosystem includes a set of special-purpose tools designed to fill in the gaps and solve the whole problem of visualization:

Panel: Assembling objects from many different libraries into a layout or app, whether in a Jupyter notebook or in a standalone servable dashboard

hvPlot: Quickly return interactive HoloViews, GeoViews or Panel objects from Pandas, Xarray, or other data structures

HoloViews: Declarative objects for instantly visualizable data, building Bokeh plots from convenient high-level specifications

GeoViews: Visualizable geographic data that that can be mixed and matched with HoloViews objects

Datashader: Rasterizing huge datasets quickly as fixed-size images

Colorcet: A wide range of perceptually uniform or large-number categorical colormaps for use with the other libraries

Holoviz对python的可视化组件进行了有机整合

HoloViz Goals:
Full functionality in browsers (not desktop)
Full interactivity (inside and out of plots)
Focus on Python users, not web programmers
Start with data, not coding
Work with data of any size
Exploit general-purpose SciPy/PyData tools
Focus on 2D primarily, with some 3D
Avoid entangling your data, code, and viz:
Same viz/analysis code in Jupyter, Python, HPC, ...
Widgets/apps in Jupyter, standalone servers, web pages
Jupyter as a tool, not part of the results
2.

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