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

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ggspatial — by Dewey Dunnington, 2 years ago

Spatial Data Framework for ggplot2

Spatial data plus the power of the ggplot2 framework means easier mapping when input data are already in the form of spatial objects.

palmerpenguins — by Allison Horst, 3 years ago

Palmer Archipelago (Antarctica) Penguin Data

Size measurements, clutch observations, and blood isotope ratios for adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made available by Dr. Kristen Gorman and the Palmer Station Long Term Ecological Research (LTER) Program.

tidyfst — by Tian-Yuan Huang, 2 months ago

Tidy Verbs for Fast Data Manipulation

A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.

rnaturalearth — by Philippe Massicotte, 2 years ago

World Map Data from Natural Earth

Facilitates mapping by making natural earth map data from < https://www.naturalearthdata.com/> more easily available to R users.

editrules — by Edwin de Jonge, a year ago

Parsing, Applying, and Manipulating Data Cleaning Rules

Please note: active development has moved to packages 'validate' and 'errorlocate'. Facilitates reading and manipulating (multivariate) data restrictions (edit rules) on numerical and categorical data. Rules can be defined with common R syntax and parsed to an internal (matrix-like format). Rules can be manipulated with variable elimination and value substitution methods, allowing for feasibility checks and more. Data can be tested against the rules and erroneous fields can be found based on Fellegi and Holt's generalized principle. Rules dependencies can be visualized with using the 'igraph' package.

mapview — by Tim Appelhans, 2 years ago

Interactive Viewing of Spatial Data in R

Quickly and conveniently create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualise true- and false-color raster images and bounding boxes.

TH.data — by Torsten Hothorn, 6 months ago

TH's Data Archive

Contains data sets used in other packages Torsten Hothorn maintains.

pdftools — by Jeroen Ooms, 4 months ago

Text Extraction, Rendering and Converting of PDF Documents

Utilities based on 'libpoppler' < https://poppler.freedesktop.org> for extracting text, fonts, attachments and metadata from a PDF file. Also supports high quality rendering of PDF documents into PNG, JPEG, TIFF format, or into raw bitmap vectors for further processing in R.

janitor — by Sam Firke, 7 months ago

Simple Tools for Examining and Cleaning Dirty Data

The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and explore duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness.

torch — by Daniel Falbel, 6 days ago

Tensors and Neural Networks with 'GPU' Acceleration

Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.