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This article will explain in detail what the Python engineer's favorite data visual chemical industry has. The editor thinks it is very practical, so I share it with you for reference. I hope you can get something after reading this article.

1. Visualization of Dengguo data (http://www.dengguobi.com/)

Dengguo data visualization BI software is a new generation of artificial intelligence data visualization large screen software, built-in rich large screen template, visual editing operation, you can create your own large screen without any experience, and is widely used in commercial, economic, medical and other fields.

Dengguo Visualization focuses on large-screen data visualization applications, and deeply optimizes the production and sharing process of visual large screens. Although on the surface, it is a drag-and-drop editing method, compared with other BI products, it is easier to use Dengguo to make a large screen, and the user experience is better.

The software provides 50 + visualization chart components, supports custom components and custom animation, can meet a variety of visualization needs, and produces a variety of cool visualization screens. Dengguo large screen template Mall provides 100 + visual large screen templates, covering various industries, replacing data with one click to generate a large screen.

The software supports the client software of the Windows/macOS/Linux system, and all operations are carried out at the local terminal, which is more secure than SAAS and does not require separate privatized deployment. At the same time, Dengguo also supports local area network version and OEM version to meet your various needs.

2 、 ECharts

ECharts, originally short for "Enterprise Charts" (Enterprise Chart), from Baidu EFE data Visualization team, is an open source visualization library implemented in JavaScript. ECharts is very powerful. It carefully optimizes the mobile end, adapts to WeChat Mini Programs, supports multiple rendering methods and front-end presentation of tens of millions of data, and even achieves barrier-free access and is friendly to people with disabilities.

3 、 D3.js

D3.js is an open source JavaScript library for data visualization and is considered to be one of the good JavaScript visualization frameworks. Developers will feel very complicated when they start to learn D3.js, but D3.js is powerful and flexible, so it is worth studying deeply. It is important to note that D3.js does not display graphics properly in older versions of IE browsers.

4 、 Plotly

Plotly is a well-known and powerful data visualization framework that can build interactive graphics and create rich and varied charts and maps. Plotly can provide relatively rare charts, such as contours, candlestick (K), and 3D charts, which are not available in most tools. In addition, Plotly's team maintains fast-growing open source visualization libraries for R, Python, and JavaScript.

5 、 Chart.js

Chart.js is an open source JavaScript library that provides designers and developers with 8 customizable ways of dynamic visualization to efficiently draw responsive charts with HTML5 Canvas. Chart.js supports mixing different chart types and plotting dates and scales, and even customizing data ranges. Chart.js also has a wealth of animation effects that can be applied when changing data or updating colors.

This is the end of this article on "what is the favorite data visual chemical industry for Python engineers to use?". I hope the above content can be helpful to you, so that you can learn more knowledge. if you think the article is good, please share it for more people to see.

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