TOC

  • tidycharts: Generate Tidy Charts Inspired by 'IBCS'
  • ggimage: Use Image in 'ggplot2'
  • modelsummary: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready
  • khroma: Colour Schemes for Scientific Data Visualization
  • loon.shiny: Automatically Create a 'Shiny' App Based on Interactive 'Loon' Widgets
  • loon: Interactive Statistical Data Visualization
  • DescTools: Tools for Descriptive Statistics
  • lessR: Less Code, More Results
  • rio: A Swiss-Army Knife for Data I/O
  • netplot: Beautiful Graph Drawing

Introduction

Each month I will describe the package that I've discovered or rediscovered and the ones that I've used the most of my time. I will start with the package used in my work and the the one that I would like to try/did not had time to use for work and also fun

Each card is organised as this

Name of the package: short description

mytags: #example tag

links
[cran package link]
[cran vignette link]
[github link]

description from the author/vignette

mynotes

tidycharts: Generate Tidy Charts Inspired by 'IBCS'

mytags: #plots

links
[cran package link] https://cran.r-project.org/web/packages/tidycharts/index.html
[cran vignette link] https://cran.r-project.org/web/packages/tidycharts/vignettes/EDA-for-palmer-penguins-data-set.html [github link] https://github.com/vedhav/tidycharts

description from the author/vignette

There is a wide range of R packages created for data visualization, but still, there was no simple and easily accessible way to create clean and transparent charts - up to now. The 'tidycharts' package enables the user to generate charts compliant with International Business Communication Standards ('IBCS'). It means unified bar widths, colors, chart sizes, etc. Creating homogeneous reports has never been that easy! Additionally, users can apply semantic notation to indicate different data scenarios (plan, budget, forecast). What's more, it is possible to customize the charts by creating a personal color pallet with the possibility of switching to default options after the experiments. We wanted the package to be helpful in writing reports, so we also made joining charts in a one, clear image possible. All charts are generated in SVG format and can be shown in the 'RStudio' viewer pane or exported to HTML output of 'knitr'/'markdown'.

mynotes

Since I love visualization I always like to try new packages. I would like to play with it soon. The svg export is a feature that I will use for sure

ggimage: Use Image in 'ggplot2'

mytags: #ggplot links
[cran package link] https://cran.r-project.org/web/packages/ggimage/index.html
[cran vignette link]
[github link] https://github.com/GuangchuangYu/ggimage [vignette link] https://yulab-smu.top/pkgdocs/ggimage.html

description from the author/vignette

Supports image files and graphic objects to be visualized in 'ggplot2' graphic system.

mynotes need to test it to try ggplot/Inkscape combo

modelsummary: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready

mytags: #models

links
[cran package link] https://cran.r-project.org/web/packages/modelsummary/index.html [vignette link] https://github.com/vincentarelbundock/modelsummary/ [github link] https://github.com/rolkra/tidydice/

description from the author/vignette

Create beautiful and customizable tables to summarize several statistical models side-by-side. Draw coefficient plots, multi-level cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and correlation matrices. This package supports dozens of statistical models, and it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel, RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr' dynamic documents.

mynotes I will need it to clean the results obtained from simulations I'm writing for an article

khroma: Colour Schemes for Scientific Data Visualization

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/tidydice/index.html [cran vignette link] https://cran.r-project.org/web/packages/khroma/vignettes/crameri.html https://cran.r-project.org/web/packages/khroma/vignettes/tol.html [github link] https://github.com/tesselle/khroma

description from the author/vignette

Colour schemes ready for each type of data (qualitative, diverging or sequential), with colours that are distinct for all people, including colour-blind readers. This package provides an implementation of Paul Tol (2018) and Fabio Crameri (2018) doi:10.5194/gmd-11-2541-2018 colour schemes for use with 'graphics' or 'ggplot2'. It provides tools to simulate colour-blindness and to test how well the colours of any palette are identifiable. Several scientific thematic schemes (geologic timescale, land cover, FAO soils, etc.) are also implemented mynotes I will use it for a tutorial about ggplot/Inkscape

loon.shiny: Automatically Create a 'Shiny' App Based on Interactive 'Loon' Widgets

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/loon.shiny/index.html [cran vignette link] https://cran.r-project.org/web/packages/loon.shiny/vignettes/introduction.html

description from the author/vignette

Package 'shiny' provides interactive web applications in R. Package 'loon' is an interactive toolkit engaged in open-ended, creative and unscripted data exploration. The 'loon.shiny' package can take 'loon' widgets and display a selfsame 'shiny' app.

mynotes Helpful for sharing plots and customize plots without scripting

loon: Interactive Statistical Data Visualization

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/loon/index.html [cran vignette link] https://cran.r-project.org/web/packages/loon/vignettes/loonPlotsAndGridGraphics.html

description from the author/vignette

An extendable toolkit for interactive data visualization and exploration.

mynotes Helpful for sharing plots and customize plots without scripting

DescTools: Tools for Descriptive Statistics

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/DescTools/index.html [cran vignette link] https://cran.r-project.org/web/packages/DescTools/vignettes/DescToolsCompanion.pdf [github link] https://github.com/AndriSignorell/DescTools/

description from the author/vignette

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.

mynotes Need to check the plotradar + missing plot

lessR: Less Code, More Results

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/lessR/index.html [cran vignette link] https://cran.r-project.org/web/packages/lessR/vignettes/utilities.html

description from the author/vignette

Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for descriptive statistics, a comprehensive regression analysis, analysis of variance and t-test, plotting including the introduced here Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, Trellis graphics and a built-in help system. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, and generation and rendering of R markdown instructions for interpretative output.

mynotes Useful for preparing tuts

rio: A Swiss-Army Knife for Data I/O

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/lessR/index.html [cran vignette link] https://cran.r-project.org/web/packages/rio/vignettes/rio.html [github link] https://github.com/leeper/rio/issues

description from the author/vignette

Streamlined data import and export by making assumptions that the user is probably willing to make:'import()' and 'export()' determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., 'stringsAsFactors=FALSE'), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, 'convert()', provides a simple method for converting between file types. mynotes to test for import spectra

netplot: Beautiful Graph Drawing

mytags: #plot #colors [cran package link] https://cran.r-project.org/web/packages/netplot/index.html [cran vignette link] https://cran.r-project.org/web/packages/netplot/vignettes/base-and-grid.html [github link] https://github.com/USCCANA/netplot/

description from the author/vignette

A graph visualization engine that puts an emphasis on aesthetics at the same time of providing default parameters that yield out-of-the-box-nice visualizations. The package is built on top of 'The Grid Graphics Package' and seamlessly work with 'igraph' and 'network' objects.

mynotes to compare with Houdini for artistic net representation