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

Found 445 packages in 0.02 seconds

polyclip — by Adrian Baddeley, 2 years ago

Polygon Clipping

R port of Angus Johnson's open source library 'Clipper'. Performs polygon clipping operations (intersection, union, set minus, set difference) for polygonal regions of arbitrary complexity, including holes. Computes offset polygons (spatial buffer zones, morphological dilations, Minkowski dilations) for polygonal regions and polygonal lines. Computes Minkowski Sum of general polygons. There is a function for removing self-intersections from polygon data.

Transition — by Mark Eisler, 21 days ago

Characterise Transitions in Test Result Status in Longitudinal Studies

Analyse data from longitudinal studies to characterise changes in values of semi-quantitative outcome variables within individual subjects, using high performance C++ code to enable rapid processing of large datasets. A flexible methodology is available for codifying these state transitions.

bigQueryR — by Mark Edmondson, 7 years ago

Interface with Google BigQuery with Shiny Compatibility

Interface with 'Google BigQuery', see < https://cloud.google.com/bigquery/> for more information. This package uses 'googleAuthR' so is compatible with similar packages, including 'Google Cloud Storage' (< https://cloud.google.com/storage/>) for result extracts.

manynet — by James Hollway, 15 days ago

Many Ways to Make, Modify, Mark, and Measure Myriad Networks

Many tools for making, modifying, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, on directed, multiplex, multimodal, signed, and other networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing networks with sensible defaults.

fuj — by Jordan Mark Barbone, a year ago

Functions and Utilities for Jordan

Provides core functions and utilities for packages and other code developed by Jordan Mark Barbone.

calibrate — by Jan Graffelman, 6 years ago

Calibration of Scatterplot and Biplot Axes

Package for drawing calibrated scales with tick marks on (non-orthogonal) variable vectors in scatterplots and biplots. Also provides some functions for biplot creation and for multivariate analysis such as principal coordinate analysis.

gridsampler — by Mark Heckmann, 9 years ago

A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies

Simulation tool to facilitate determination of required sample size to achieve category saturation for studies using multiple repertory grids in conjunction with content analysis.

autodb — by Mark Webster, 5 months ago

Automatic Database Normalisation for Data Frames

Automatic normalisation of a data frame to third normal form, with the intention of easing the process of data cleaning. (Usage to design your actual database for you is not advised.) Originally inspired by the 'AutoNormalize' library for 'Python' by 'Alteryx' (< https://github.com/alteryx/autonormalize>), with various changes and improvements. Automatic discovery of functional or approximate dependencies, normalisation based on those, and plotting of the resulting "database" via 'Graphviz', with options to exclude some attributes at discovery time, or remove discovered dependencies at normalisation time.

mvbutils — by Mark V. Bravington, 7 years ago

Workspace Organization, Code and Documentation Editing, Package Prep and Editing, Etc

Hierarchical workspace tree, code editing and backup, easy package prep, editing of packages while loaded, per-object lazy-loading, easy documentation, macro functions, and miscellaneous utilities. Needed by debug package.

colleyRstats — by Mark Colley, 3 months ago

Functions to Streamline Statistical Analysis and Reporting

Built upon popular R packages such as 'ggstatsplot' and 'ARTool', this collection offers a wide array of tools for simplifying reproducible analyses, generating high-quality visualizations, and producing 'APA'-compliant outputs. The primary goal of this package is to significantly reduce repetitive coding efforts, allowing you to focus on interpreting results. Whether you're dealing with ANOVA assumptions, reporting effect sizes, or creating publication-ready visualizations, this package makes these tasks easier.