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Vue Big Screen

一个基于 vue、datav、Echart 框架的大数据可视化(大屏展示)模板,实现大数据可视化。通过 vue 组件实现数据动态刷新渲染,内部图表可自由替换。部分图表使用 DataV 自带组件,可自由进行更改(ps:最新的更新请前往码云查看,下面有链接)。

Vue Big Screen

一个基于 vue、datav、Echart 框架的大数据可视化(大屏展示)模板,实现大数据可视化。通过 vue 组件实现数据动态刷新渲染,内部图表可自由替换。部分图表使用 DataV 自带组件,可自由进行更改(ps:最新的更新请前往码云查看,下面有链接)。

Author Avatar Theme by l-noodle
Github Stars Github Stars: 795
Last Commit Last Commit: Jun 20, 2020 -
First Commit Created: Aug 27, 2024 -
Vue Big Screen screenshot

Overview

This “Data Dashboard Project” built on Vue, DataV, and Echart frameworks is an innovative approach to data visualization. With its capability for dynamic data rendering through Vue components, this project allows users to display real-time data effectively. The internal charts are designed for easy replacement, giving users flexibility in how they present information.

Utilizing DataV components, this project offers customization options for charts and visual elements. The architecture leverages Vue CLI along with modern build tools, ensuring a scalable and efficient development environment. It’s a valuable solution for those looking to implement vivid and interactive data displays.

Features

  • Dynamic Data Rendering: Utilizes Vue components to allow for real-time updates and dynamic rendering of data visuals.
  • Flexible Chart Replacement: Internal charts can be easily swapped out, providing versatility in presenting different datasets.
  • Customizable Components: Leverage DataV’s built-in components to customize charts as per project needs.
  • Efficient Build Tools: Built using Vue CLI 3.0, Webpack 4.0, ensuring modern development practices are in place.
  • Global Registration Option: Supports global registration for components, although it may increase build size; on-demand imports are recommended for efficiency.
  • Optimized Performance: Utilizes npm 6.13 and Node 12.16 for an optimized development environment, ensuring speed and responsiveness.
  • Documentation Resources: Comprehensive guides and documentation are available for users to explore and understand the functionalities better.