Displaying 1 to 20 from 353 results

gganimate - A Grammar of Animated Graphics

  •    R

gganimate extends the grammar of graphics as implemented by ggplot2 to include the description of animation. It does this by providing a range of new grammar classes that can be added to the plot object in order to customise how it should change with time. In this example we see the use of transition_time() which can be used with continuous variables such as year. With this transition it is not necessary to provide transition and state length as the "transition variable" provides this directly (e.g. it should take twice as long to transition between 1980 and 1990 compared to 2000 to 2005). We also see the use of string literal interpolation in titles. gganimate lets you specify variables to evaluate inside titles and different transitions provide different type of information to use.

patchwork - The Composer of ggplots

  •    R

The goal of patchwork is to make it ridiculously simple to combine separate ggplots into the same graphic. As such it tries to solve the same problem as gridExtra::grid.arrange() and cowplot::plot_grid but using an API that incites exploration and iteration.

sparklyr - R interface for Apache Spark

  •    R

If you use the RStudio IDE, you should also download the latest preview release of the IDE which includes several enhancements for interacting with Spark (see the RStudio IDE section below for more details). The returned Spark connection (sc) provides a remote dplyr data source to the Spark cluster.

networkD3 - D3 JavaScript Network Graphs from R

  •    R

This README includes information on set up and a number of basic examples. For more information see the package's main page. networkD3 began as a port of d3Network package to the htmlwidgets framework. d3Network is no longer supported.




ggrepel - :round_pushpin: Repel overlapping text labels away from each other.

  •    R

Text labels repel away from each other, away from data points, and away from edges of the plotting area. Please submit an issue to report bugs or ask questions.

efficientR - Efficient R programming: a book

  •    TeX

The text and code for the forthcoming O'Reilly book: Efficient R programming. Pull requests and general comments are welcome. For details on how to build this book, please see the Appendix.

hrbrthemes - :lock_with_ink_pen: Opinionated, typographic-centric ggplot2 themes and theme components

  •    R

This is a very focused package that provides typography-centric themes and theme components for ggplot2. It’s a an extract/riff of hrbrmisc created by request. The core theme: theme_ipsum (“ipsum” is Latin for “precise”) uses Arial Narrow which should be installed on practically any modern system, so it’s “free”-ish. This font is condensed, has solid default kerning pairs and geometric numbers. That’s what I consider the “font trifecta” must-have for charts. An additional quality for fonts for charts is that they have a diversity of weights. Arial Narrow (the one on most systems, anyway) does not have said diversity but this quality is not (IMO) a “must have”.

highcharter - R wrapper for highcharts based on htmlwidgets

  •    R

R wrapper for highcharts. highcharter bring all the highcharts capabilites so it is recommended know how highcharts API works to take a major advantage of this package. You can look some demos charts and explore chart types, syntax and all what highcharts can do. Highcharter has a dependency on Highcharts, a commercial JavaScript charting library. Highcharts offers both a commercial license as well as a free non-commercial license. Please review the licensing options and terms before using this software, as the highcharter license neither provides nor implies a license for Highcharts.


shinyjs - Easily improve the user experience of your Shiny apps in seconds

  •    R

shinyjs lets you perform common useful JavaScript operations in Shiny apps that will greatly improve your apps without having to know any JavaScript. Examples include: hiding an element, disabling an input, resetting an input back to its original value, delaying code execution by a few seconds, and many more useful functions for both the end user and the developer. shinyjs can also be used to easily call your own custom JavaScript functions from R.

engsoccerdata - English and European soccer results 1871-2017

  •    R

This R package is mainly a repository for complete soccer datasets, along with some built-in functions for analyzing parts of the data. Currently I include three English ones (League data, FA Cup data, Playoff data - described below), several European leagues (Spain, Germany, Italy, Holland, France, Belgium, Portugal, Turkey, Scotland, Greece) as well as South Africa and MLS. Free to use for non-commerical use. Compiled by James Curley.

ggalt - :earth_americas: Extra Coordinate Systems, Geoms, Statistical Transformations & Scales for 'ggplot2'

  •    R

A compendium of ‘geoms’, ‘coords’, ‘stats’, scales and fonts for ‘ggplot2’, including splines, 1d and 2d densities, univariate average shifted histograms, a new map coordinate system based on the ‘PROJ.4’-library and the ‘StateFace’ open source font ‘ProPublica’.

usethis - Set up commonly used 📦 components

  •    R

usethis is a workflow package: it automates repetitive tasks that arise during project setup and development, both for R packages and non-package projects. Most use_*() functions operate on the active project: literally, a directory on your computer. If you’ve just used usethis to create a new package or project, that will be the active project. Otherwise, usethis verifies that current working directory is or is below a valid project directory and that becomes the active project. Use proj_get() or proj_sitrep() to manually query the project and read more in the docs.

ggforce - Accelerating ggplot2

  •    R

ggforce is a package aimed at providing missing functionality to ggplot2 through the extension system introduced with ggplot2 v2.0.0. Broadly speaking ggplot2 has been aimed primarily at explorative data visualization in order to investigate the data at hand, and less at providing utilities for composing custom plots a la D3.js. ggforce is mainly an attempt to address these "shortcoming" (design choices might be a better description). The goal is to provide a repository of geoms, stats, etc. that are as well documented and implemented as the official ones found in ggplot2. The inclusion of any geom, stat, position etc in ggforce is not necessarily a recommendation of their use. ggplot2 has been successful in being opinionated about what functionality should be available. This is good as it insulates the user from making bad decisions when analyzing their data (to a certain degree), but it also makes it difficult to develop novel visualizations using the ggplot2 API. ggforce on the other hand positions itself closer to the "anything goes - the user is responsible for the quality of the output". Be very aware of this responsibility! Bad visualizations lie about, distorts, and obscure the data behind them, both to you and the ones you share your visualizations with.

tweenr - Interpolate your data

  •    R

tweenr is a small package that makes it easy to interpolate your data between different states, specifying the length of each change, the easing of the transition and how many intermediary steps should be generated. tweenr works particularly well with gganimate but can be used for any case where interpolation of data is needed. All functions are vectorized so in any case you'll get better performance than using approx and colorRamp. tween_states takes a list of data.frames, each representing a state of your data, and interpolates the transition between them. Only the first data.frame needs to be full, the following only needs to contain the columns that shows any change. It is possible to specify the length of each individual transition, as well as the length of the pause at each state. Each transition can also have an easing function assiciated with it that describes how the transition should progress.

UpSetR - An R implementation of the UpSet set visualization technique published by Lex, Gehlenborg, et al

  •    R

UpSetR generates static UpSet plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. For further details about the original technique see the UpSet website. You can also check out the UpSetR shiny app. Here is the source code for the shiny wrapper.

ggpage - Creates Page Layout Visualizations in R

  •    R

ggpage is a package to create pagestyled visualizations of text based data. It uses ggplot2 and final returns are ggplot2 objects. In this new version I have worked to include a lot of use cases that wasn’t available in the first version. These new elements are previewed in the vignette.

r-color-palettes - Comprehensive list of color palettes available in r

  •    R

The goal of this repository is to have a one stop destination for anyone looking for a color palette to use in r. If you would like to help/contribute please feel free post an issue, PR or send a email to emilhhvitfeldt@gmail.com. Further down the page is all the palettes available in the R ecosystem ordered alphabetically by package name. A list of palettes ordered by type can be found here Type sorted palettes to shorten the length of this page.

datascience-box - Data Science Course in a Box

  •    HTML

This introductory data science course that is our (working) answer to these questions. The courses focuses on data acquisition and wrangling, exploratory data analysis, data visualization, and effective communication and approaching statistics from a model-based, instead of an inference-based, perspective. A heavy emphasis is placed on a consitent syntax (with tools from the tidyverse), reproducibility (with R Markdown) and version control and collaboration (with git/GitHub). We help ease the learning curve by avoiding local installation and supplementing out-of-class learning with interactive tools (like learnr tutorials). By the end of the semester teams of students work on fully reproducible data analysis projects on data they acquired, answering questions they care about. This repository serves as a "data science course in a box" containing all materials required to teach (or learn from) the course described above.

webchem - Chemical Information from the Web

  •    R

webchem is a R package to retrieve chemical information from the web. This package interacts with a suite of web APIs to retrieve chemical information.The functions in the package that hit a specific API have a prefix and suffix separated by an underscore (prefix_suffix()) They follow the format of source_functionality, e.g.cs_compinfo uses ChemSpider to retrieve compound informations.





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