{ "info": { "author": "Stephen Grubb", "author_email": "stevegrubb@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Web Environment", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Financial and Insurance Industry", "Intended Audience :: Healthcare Industry", "Intended Audience :: Information Technology", "Intended Audience :: Legal Industry", "Intended Audience :: Manufacturing", "Intended Audience :: Other Audience", "Intended Audience :: Science/Research", "Intended Audience :: System Administrators", "Intended Audience :: Telecommunications Industry", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 2.7", "Topic :: Internet :: WWW/HTTP :: Dynamic Content", "Topic :: Internet :: WWW/HTTP :: WSGI :: Application", "Topic :: Multimedia :: Graphics", "Topic :: Multimedia :: Graphics :: Presentation", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Scientific/Engineering :: Medical Science Apps.", "Topic :: Scientific/Engineering :: Visualization", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Utilities" ], "description": "SVGdatashapes is a compact set of python functions \nfor creating many types of plots and data displays in SVG for use in web pages. \n\nFor full info and examples see: https://pepprseed.github.io/svgdatashapes \n\nGeneral purpose, useful in areas such as biomedical, scientific, business, process monitoring, report generation. \nPlenty of control over legends, tooltips, colors, transparency, and many other appearance details. \nIt has no package dependencies, and can work nicely in frameworks such as Flask and Bootstrap. \nNo javascript, CSS, DOM, or SVG knowledge is required. \n\nProduce many types of bargraphs, lineplots, curves, bands, scatterplots, pie graphs, heatmaps, boxplots, \nhistograms, multipanel displays, \nand other data displays like windbarbs and Secchi depth graphs. Plot from your numeric, categorical, or date/time data. \n\nSVGdatashapes produces attractive results for many typical straightforward graphing / data display needs, as can be seen \nin the examples. The approach is procedural and the code is relatively simple and agile (click on examples to see code). \nIt supports some basic \"reactive\" things: tooltips, clickthru, hyperlinks, element hide/show with js. It does some basic \nstat / computational things: data ranges, frequency distributions, mean and SD, quartiles for boxplots. \nFor a given project, developers should judge whether SVGdatashapes is sufficient, or if more involved approaches \n(such as D3, Plotly, Numpy, R ggplot) are necessary. \n\nSVGdatashapes renders its results in SVG. All modern web browsers support viewing and printing of SVG graphics. \nSVG is a good format for web-based data displays and line art because it is vector-based and has full support for \ngood fonts, text in any direction, transparency, as well as tooltip and hyperlink support. SVG can share CSS styling \nfrom the host web page and can use the full range of html special characters to get Greek letters, etc. \n(SVGdatashapes also supports and for superscripts and subscripts). \n\nYou can include a chunk of SVG code directly into your html (referred to as an \"inline SVG\"). Or, you can put the SVG in a separate file and reference it using an tag. (We do it both ways on our web site.) 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