简单但强大的交互式数据分析在R与R/LinekdCharts
Svetlana Ovchinnikova1, Simon Anders2
1Center for Molecular Biology and BioQuant Center of the University of Heidelberg, Heidelberg, Germany.
Genome biology
|February 5, 2024
概括
R/LinkedCharts通过链接概述和细节可视化来简化探索性数据分析. 这个R包允许研究人员轻松创建交互式,出版品质的数据可视化,使用最小的代码.
科学领域:
- 生物信息学是一种生物信息学.
- 数据可视化 数据可视化
- 计算生物学 计算生物学
背景情况:
- 探索性数据分析 (EDA) 对于数据丰富的测试至关重要.
- 目前的EDA方法通常需要复杂的,代的可视化调整.
- 桥梁概述和详细的数据视图可能是具有挑战性的.
研究的目的:
- 为简化EDA引入R/LinkedCharts,这是一个新的R包.
- 为了促进链接的创建,交互式可视化.
- 简化生成出版品质的数据探索工具.
主要方法:
- 在R.R.中开发R/LinkedCharts框架.
- 实施一个连接多个图表的系统.
- 专注于尽量减少复杂可视化的编码工作.
主要成果:
- R/LinkedCharts允许使用最少的代码创建链接图表.
- 该框架支持交互式数据探索,将概述和细节视图联系起来.
- 生成的可视化适合抛光到出版质量.
结论:
- 在EDA中,R/LinkedCharts显著简化了复杂的可视化任务.
- 该套件提高了探索数据丰富的测试结果的效率.
- 它为生成交互式,高质量的科学图形提供了一个强大的工具.
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