{ "_id": "6a102c45acfb0bcc41c92ffe", "Package": "DataVisualizations", "Type": "Package", "Title": "Visualizations of High-Dimensional Data", "Version": "1.4.0", "Date": "2025-10-31", "Authors@R": "c(person(\"Michael\", \"Thrun\", email= \"m.thrun@gmx.net\",role=c(\"aut\",\"cre\",\"cph\"), comment = c(ORCID = \"0000-0001-9542-5543\")),person(\"Felix\", \"Pape\",role=c(\"aut\",\"rev\")),person(\"Onno\", \"Hansen-Goos\",role=c(\"ctr\",\"ctb\")),person(\"Quirin\", \"Stier\",role=c(\"ctb\",\"rev\"), comment = c(ORCID = \"0000-0002-7896-4737\")),person(\"Hamza\", \"Tayyab\",role=c(\"ctr\",\"ctb\")),person(\"Luca\", \"Brinkmann\",role=c(\"ctr\",\"ctb\")),person(\"Dirk\", \"Eddelbuettel\",role=c(\"ctb\")),person(\"Winston\", \"Chang\",role=c(\"ctb\")),person(\"Craig\", \"Varrichio\",role=c(\"ctb\")),person(\"Alfred\", \"Ultsch\",role=c(\"dtc\",\"ctb\",\"ctr\")))", "Maintainer": "Michael Thrun ", "Description": "Gives access to data visualisation methods that are\nrelevant from the data scientist's point of view. The flagship\nidea of 'DataVisualizations' is the mirrored density plot\n(MD-plot) for either classified or non-classified multivariate\ndata published in Thrun, M.C. et al.: \"Analyzing the Fine\nStructure of Distributions\" (2020), PLoS ONE,\n. The MD-plot outperforms the\nbox-and-whisker diagram (box plot), violin plot and bean plot\nand geom_violin plot of ggplot2. Furthermore, a collection of\nvarious visualization methods for univariate data is provided.\nIn the case of exploratory data analysis, 'DataVisualizations'\nmakes it possible to inspect the distribution of each feature\nof a dataset visually through a combination of four methods.\nOne of these methods is the Pareto density estimation (PDE) of\nthe probability density function (pdf). Additionally,\nvisualizations of the distribution of distances using PDE, the\nscatter-density plot using PDE for two variables as well as the\nShepard density plot and the Bland-Altman plot are presented\nhere. Pertaining to classified high-dimensional data, a number\nof visualizations are described, such as f.ex. the heat map and\nsilhouette plot. A political map of the world or Germany can be\nvisualized with the additional information defined by a\nclassification of countries or regions. By extending the\npolitical map further, an uncomplicated function for a\nChoropleth map can be used which is useful for measurements\nacross a geographic area. For categorical features, the Pie\ncharts, slope charts and fan plots, improved by the ABC\nanalysis, become usable. More detailed explanations are found\nin the book by Thrun, M.C.: \"Projection-Based Clustering\nthrough Self-Organization and Swarm Intelligence\" (2018)\n.", "License": "GPL-3", "SystemRequirements": "GNU make, C++17", "LazyLoad": "yes", "LazyData": "TRUE", "LazyDataCompression": "xz", "URL": "https://www.deepbionics.org/", "VignetteBuilder": "knitr", "BugReports": "https://github.com/Mthrun/DataVisualizations/issues", "Config/pak/sysreqs": "make libicu-dev", "Repository": "https://mthrun.r-universe.dev", "Date/Publication": "2025-11-01 09:41:03 UTC", "RemoteUrl": "https://github.com/mthrun/datavisualizations", "RemoteRef": "HEAD", "RemoteSha": "eb936457b0eedf457e0abe264dc15f0e4eabacdc", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-22 10:03:41 UTC", "User": "root" }, "Author": "Michael Thrun [aut, cre, cph] (ORCID:\n),\nFelix Pape [aut, rev],\nOnno Hansen-Goos [ctr, ctb],\nQuirin Stier [ctb, rev] (ORCID:\n),\nHamza Tayyab [ctr, ctb],\nLuca Brinkmann [ctr, ctb],\nDirk Eddelbuettel [ctb],\nWinston Chang [ctb],\nCraig Varrichio [ctb],\nAlfred Ultsch [dtc, ctb, ctr]", "MD5sum": "4f2757364d2139242f822e794f7c38c5", "_user": "mthrun", "_type": "src", "_file": "DataVisualizations_1.4.0.tar.gz", "_fileid": "19ddf0a0816fb08b523176a817b2902d8ccd9a31ede5bcdcbe9454a1586d95fa", "_filesize": 18501237, "_sha256": "19ddf0a0816fb08b523176a817b2902d8ccd9a31ede5bcdcbe9454a1586d95fa", "_created": "2026-05-22T10:03:41.000Z", "_published": "2026-05-22T10:13:25.135Z", "_distro": "noble", "_jobs": [ { "job": 77358641439, "time": 246, "config": "linux-devel-arm64", "r": "4.7.0", "check": "ERROR", "artifact": "7158012695" }, { "job": 77358641291, "time": 238, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "ERROR", "artifact": "7158010200" }, { "job": 77358641370, "time": 238, "config": "linux-release-arm64", "r": "4.6.0", "check": "ERROR", "artifact": "7158010166" }, { "job": 77358641410, "time": 277, "config": "linux-release-x86_64", "r": "4.6.0", "check": "ERROR", "artifact": "7158022182" }, { "job": 77358641567, "time": 192, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "ERROR", "artifact": "7157995742" }, { "job": 77358641369, "time": 474, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "ERROR", "artifact": "7158082525" }, { "job": 77358641400, "time": 210, "config": "macos-release-arm64", "r": "4.6.0", "check": "ERROR", "artifact": "7158001370" }, { "job": 77358641442, "time": 356, "config": "macos-release-x86_64", "r": "4.6.0", "check": "ERROR", "artifact": "7158046935" }, { "job": 77357734936, "time": 350, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7157936611" }, { "job": 77358641498, "time": 152, "config": "wasm-release", "r": "4.6.0", "check": "FAIL", "artifact": "" }, { "job": 77358641331, "time": 252, "config": "windows-devel", "r": "4.7.0", "check": "ERROR", "artifact": "7158014591" }, { "job": 77358641383, "time": 261, "config": "windows-oldrel", "r": "4.5.3", "check": "ERROR", "artifact": "7158017807" }, { "job": 77358641427, "time": 231, "config": "windows-release", "r": "4.6.0", "check": "ERROR", "artifact": "7158008165" } ], "_buildurl": "https://github.com/r-universe/mthrun/actions/runs/26281250318", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/mthrun/datavisualizations", "_commit": { "id": "eb936457b0eedf457e0abe264dc15f0e4eabacdc", "author": "Mthrun ", "committer": "Mthrun ", "message": "1.4.0 on cran\n", "time": 1761990063 }, "_maintainer": { "name": "Michael Thrun", "email": "m.thrun@gmx.net", "login": "mthrun", "description": "Dr. habil. 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plot" ], "topics": [ "Classplot" ] }, { "page": "CombineCols", "title": "Combine vectors of various lengths", "topics": [ "cbind_fill", "CombineCols" ] }, { "page": "CombineRows", "title": "Combine matrices of various lengths", "topics": [ "CombineRows", "rbind_fill" ] }, { "page": "Crosstable", "title": "Crosstable plot", "topics": [ "Crosstable" ] }, { "page": "DefaultColorSequence", "title": "Default color sequence for plots", "topics": [ "DefaultColorSequence" ] }, { "page": "DensityContour", "title": "Contour plot of densities", "concept": [ "Density Estimation", "contour plot", "density plot", "contour density plot" ], "topics": [ "DensityContour" ] }, { "page": "DensityScatter", "title": "Scatter plot with densities", "concept": [ "Density Estimation", "scatter plot", "density plot", "scatter density plot" ], "topics": [ "DensityScatter" ] }, { "page": "DiagnosticAbility4Classifiers", "title": "DiagnosticAbility4Classifiers", "topics": [ "DiagnosticAbility4Classifiers" ] }, { "page": "DrawWorldWithCls", "title": "Plot a classificated world map", "topics": [ "DrawWorldWithCls" ] }, { "page": "DualaxisClassplot", "title": "Dualaxis Classplot", "topics": [ "DualaxisClassplot" ] }, { "page": "DualaxisLinechart", "title": "DualaxisLinechart", "topics": [ "DualaxisLinechart" ] }, { "page": "estimateDensity2D", "title": "estimateDensity2D", "concept": [ "estimate densities in 2D" ], "topics": [ "estimateDensity2D" ] }, { "page": "Fanplot", "title": "The fan plot", "topics": [ "Fanplot" ] }, { "page": "FundamentalData_Q1_2018", "title": "Fundamental Data of the 1st Quarter in 2018", "topics": [ "FundamentalData_Q1_2018" ] }, { "page": "GermanPostalCodesShapes", "title": "GermanPostalCodesShapes", "topics": [ "GermanPostalCodesShapes" ] }, { "page": "GoogleMapsCoordinates", "title": "Google Maps with marked coordinates", "topics": [ "GoogleMapsCoordinates" ] }, { "page": "Heatmap", "title": "Heatmap for Clustering", "topics": [ "Heatmap" ] }, { "page": "HeatmapColors", "title": "Default color sequence for plots", "topics": [ "HeatmapColors" ] }, { "page": "InspectBoxplots", "title": "Inspect Boxplots", "topics": [ "InspectBoxplots" ] }, { "page": "InspectCorrelation", "title": "Inspect the Correlation", "topics": [ "InspectCorrelation" ] }, { "page": "InspectDistances", "title": "Inspection of Distance-Distribution", "topics": [ "InspectDistances" ] }, { "page": "InspectScatterplots", "title": "Pairwise scatterplots and optimal histograms", "topics": [ "InspectScatterplots" ] }, { "page": "InspectStandardization", "title": "QQplot of Data versus Normalized Data", "topics": [ "InspectStandardization" ] }, { "page": "InspectVariable", "title": "Visualization of Distribution of one variable", "topics": [ "InspectVariable" ] }, { "page": "ITS", "title": "Income Tax Share", "topics": [ "ITS" ] }, { "page": "JitterUniqueValues", "title": "Jitters Unique Values", "topics": [ "JitterUniqueValues" ] }, { "page": "Lsun3D", "title": "Lsun3D inspired by FCPS [Thrun/Ultsch, 2020] introduced in [Thrun, 2018]", "topics": [ "Lsun3D" ] }, { "page": "MAplot", "title": "Minus versus Add plot", "topics": [ "MAplot" ] }, { "page": "MDplot", "title": "Mirrored Density plot (MD-plot)", "concept": [ "violin plot", "Mirrored Density plot", "Mirrored Density", "probability density function", "bean plot", "vase plot", "box plot", "box whisker diagramm", "schematic plot" ], "topics": [ "MDplot" ] }, { "page": "MDplot4multiplevectors", "title": "Mirrored Density plot (MD-plot)for Multiple Vectors", "topics": [ "MDplot4multiplevectors" ] }, { "page": "MDstrips", "title": "High-dimensional Density Strips based on Pareto Density Estimation", "topics": [ "MDstrips" ] }, { "page": "meanrobust", "title": "Robust Empirical Mean Estimation", "topics": [ "Meanrobust", "meanrobust" ] }, { "page": "MTY", "title": "Muncipal Income Tax Yield", "topics": [ "MTY" ] }, { "page": "multiplot", "title": "Plot multiple ggplots objects in one panel", "topics": [ "Multiplot" ] }, { "page": "OpposingViolinBiclassPlot", "title": "OpposingViolinBiclassPlot", "topics": [ "OpposingViolinBiclassPlot" ] }, { "page": "OptimalNoBins", "title": "Optimal Number Of Bins", "topics": [ "OptimalNoBins" ] }, { "page": "ParetoDensityEstimation", "title": "Pareto Density Estimation V3", "topics": [ "ParetoDensityEstimation" ] }, { "page": "ParetoRadius", "title": "ParetoRadius for distributions", "topics": [ "ParetoRadius" ] }, { "page": "ParetoRadius_fast", "title": "Fast ParetoRadius for distributions", "topics": [ "ParetoRadius_fast" ] }, { "page": "PDEnormrobust", "title": "PDEnormrobust", "topics": [ "PDEnormrobust" ] }, { "page": "PDEplot", "title": "PDE plot", "topics": [ "PDEplot" ] }, { "page": "PDEstrip", "title": "1D Density Strip based on Pareto Density Estimation (PDE)", "concept": [ "Pareto Density Estimation", "heat strip", "violin alternative" ], "topics": [ "PDEstrip" ] }, { "page": "Piechart", "title": "The pie chart", "topics": [ "Piechart" 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