Материал из Common History development
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| | [[Category:Analysis tools]] | | [[Category:Analysis tools]] |
| − | [[lw:Category:Visualization]] | + | [[aw:Category:Visualization]] |
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| − | = [http://vincebuffalo.org/blog/2012/11/14/my-first-recommendation-to-new-scientific-coders-learn-visualization.html How do I Learn Visualization?] =
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| − | *[http://www.ggobi.org/ ggobi] is a useful system for high-dimension visualization.
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| − | *[http://cran.r-project.org/web/packages/lattice/index.html lattice] was the first graphics package for [[R]] I learned, and even though I use ggplot2 primarily now, it is still useful.
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| − | == finance ==
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| − | *http://dygraphs.com/gallery
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| − | *http://vega.github.io/
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| − | Vega is a declarative format for creating, saving, and [[Design data exchange formats|sharing]] visualization designs. With Vega, visualizations are described in JSON, and generate interactive views using either HTML5 [[aw:Canvas]] or [[aw:SVG]]. Is used in MediaWiki https://www.mediawiki.org/wiki/Extension:Graph
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| − | == bioinformatics ==
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| − | *[http://software.broadinstitute.org/software/igv/ igv] - desktop tool for interactive exploration of large, integrated genomic datasets
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| − | *[http://www.bioconductor.org/packages/2.11/bioc/html/ggbio.html ggbio] ... Learning to use genome browsers, track formats (BED, WIG, GTF), and read visualization programs (such as IGV)
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| − | *[http://biopython.org/wiki/Getting_Started biopython]
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Версия 14:52, 29 сентября 2017
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