Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 553 packages in 0.62 seconds

rgl — by Duncan Murdoch, 2 months ago

3D Visualization Using OpenGL

Provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.

igraph — by Gabor Csardi, 2 years ago

Network Analysis and Visualization

Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

scales — by Hadley Wickham, 6 months ago

Scale Functions for Visualization

Graphical scales map data to aesthetics, and provide methods for automatically determining breaks and labels for axes and legends.

vcd — by David Meyer, 7 months ago

Visualizing Categorical Data

Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).

ROCR — by Tobias Sing, 2 years ago

Visualizing the Performance of Scoring Classifiers

ROC graphs, sensitivity/specificity curves, lift charts, and precision/recall plots are popular examples of trade-off visualizations for specific pairs of performance measures. ROCR is a flexible tool for creating cutoff-parameterized 2D performance curves by freely combining two from over 25 performance measures (new performance measures can be added using a standard interface). Curves from different cross-validation or bootstrapping runs can be averaged by different methods, and standard deviations, standard errors or box plots can be used to visualize the variability across the runs. The parameterization can be visualized by printing cutoff values at the corresponding curve positions, or by coloring the curve according to cutoff. All components of a performance plot can be quickly adjusted using a flexible parameter dispatching mechanism. Despite its flexibility, ROCR is easy to use, with only three commands and reasonable default values for all optional parameters.

klaR — by Uwe Ligges, 3 years ago

Classification and visualization

Miscellaneous functions for classification and visualization developed at the Fakultaet Statistik, Technische Universitaet Dortmund

ggmap — by David Kahle, a year ago

Spatial Visualization with ggplot2

A collection of functions to visualize spatial data and models on top of static maps from various online sources (e.g Google Maps and Stamen Maps). It includes tools common to those tasks, including functions for geolocation and routing.

rasterVis — by Oscar Perpinan Lamigueiro, 4 months ago

Visualization Methods for Raster Data

Methods for enhanced visualization and interaction with raster data. It implements visualization methods for quantitative data and categorical data, both for univariate and multivariate rasters. It also provides methods to display spatiotemporal rasters, and vector fields. See the website for examples.

corrplot — by Taiyun Wei, a year ago

Visualization of a Correlation Matrix

A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.

multcompView — by Luciano Selzer, 2 years ago

Visualizations of Paired Comparisons

Convert a logical vector or a vector of p-values or a correlation, difference, or distance matrix into a display identifying the pairs for which the differences were not significantly different. Designed for use in conjunction with the output of functions like TukeyHSD, dist{stats}, simint, simtest, csimint, csimtest{multcomp}, friedmanmc, kruskalmc{pgirmess}.