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2 dépôts

Awesome GitHub RepositoriesChart Rendering Optimizations

Renders charts with thousands of data points while keeping interactions fast through configurable rendering modes and boost options.

Distinct from Large-Dataset Dashboards: Distinct from Large-Dataset Dashboards: focuses on chart rendering with thousands of data points, not dashboards with multidimensional filtering on tabular datasets.

Explore 2 awesome GitHub repositories matching data & databases · Chart Rendering Optimizations. Refine with filters or upvote what's useful.

Awesome Chart Rendering Optimizations GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • justineo/vue-echartsAvatar de Justineo

    Justineo/vue-echarts

    10,720Voir sur GitHub↗

    vue-echarts is a declarative charting wrapper and Vue.js component for the Apache ECharts library. It functions as a data visualization library that maps configurations and data updates to a rendering engine, enabling the embedding of interactive graphs and charts as reusable web components. The project provides a system for managing visual consistency through theme configuration and context-based injection. It allows for deep customization of the visualization interface, including the use of scoped slots to render custom HTML markup within tooltips and the construction of complex graphic ele

    Optimizes rendering efficiency by calculating partial configuration updates to avoid full chart re-renders.

    TypeScript
    Voir sur GitHub↗10,720
  • naver/billboard.jsAvatar de naver

    naver/billboard.js

    5,980Voir sur GitHub↗

    billboard.js is a JavaScript charting library built on D3.js that renders interactive data visualizations from a single declarative configuration object. It supports a wide range of chart types including bar, line, pie, scatter, area, spline, step, candlestick, funnel, gauge, heatmap, radar, polar, treemap, bubble, donut, and sparkline charts, and can overlay multiple chart types within a single visualization. The library offers an opt-in Canvas rendering mode for improved performance with large datasets and high-density axis displays, alongside its standard SVG-based rendering. The library d

    Renders charts with thousands of data points while keeping interactions fast through configurable rendering modes.

    TypeScript
    Voir sur GitHub↗5,980
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