https://github.com/gagniuc/native-js-charts

The projects in this repository show a series of js charts of two types. Both of these types use the HTML5 canvas object. The first type of chart provides a normal linear plot and the second type is a circular model.
https://github.com/gagniuc/native-js-charts

canvas chart chartjs charts data-visualization effects html5 javascript js linear native nativescript plot plotly round visualization

Last synced: 3 months ago
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The projects in this repository show a series of js charts of two types. Both of these types use the HTML5 canvas object. The first type of chart provides a normal linear plot and the second type is a circular model.

• Host: GitHub
• URL: https://github.com/gagniuc/native-js-charts
• Owner: Gagniuc
• License: mit
• Created: 2021-10-28T21:30:56.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-07-22T14:50:04.000Z (over 2 years ago)
• Last Synced: 2024-10-09T22:23:58.634Z (3 months ago)
• Topics: canvas, chart, chartjs, charts, data-visualization, effects, html5, javascript, js, linear, native, nativescript, plot, plotly, round, visualization
• Language: HTML
• Homepage:
• Size: 4.78 MB
• Stars: 6
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE.md

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# native - Java Script Charts

The projects in this repository show a series of js charts of two types. Both of these types use the HTML5 canvas object. The first type of chart provides a normal linear plot and probably shows the shortest source code for a chart made in javascript. The second type of chart has a circular design and contains many physical effects in relation to  elasticity. These charts can be further developed for different websites that require data views in a context that allows different effects. These native Charts in Javascript, were published in the supplementary materials of the book entitled Algorithms in Bioinformatics: Theory and Implementation.



















# References

- Paul A. Gagniuc. Algorithms in Bioinformatics: Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961.