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Recusos de R, RKWard, Rmd, QC...
Página principal
rk plug-ins
Data sets
Recusos de R, RKWard, Rmd, QC...
Página principal
rk plug-ins
Data sets
More
Página principal
rk plug-ins
Data sets
rk plug-ins
Plug-ins de RKWard en github
AlfCano - Repositories
GitHub - AlfCano/rk.gsub.sub: An RKWard plugin that provides a graphical user interface (GUI) for the base R functions `sub()` and `gsub()`. This tool allows users to perform powerful pattern finding and replacement on character vectors without needing to write code.
GitHub - AlfCano/rk.gtsummary: An RKWard plugin to generate summary tables using the 'gtsummary' package, supporting both standard data.frames (tbl_summary) and survey design objects (tbl_svysummary).
GitHub - AlfCano/rk.cSplit: This plugin provides a robust graphical user interface within RKWard for splitting columns that contain delimited or concatenated data. It serves as a user-friendly front-end for the powerful `cSplit()` function from the `splitstackshape` package.
GitHub - AlfCano/rk.forcats: This package provides a suite of RKWard plugins that create a graphical user interface for common and powerful functions from the popular `forcats` R package. It is designed to make factor manipulation—a common but often tedious task in R—more accessible and intuitive for RKWard users.
GitHub - AlfCano/rk.pivot.reshape: This plugin package provides two powerful data reshaping tools within the RKWard graphical user interface, making common data wrangling tasks more accessible. It acts as a friendly front-end for two core functions from the popular `tidyr` package
GitHub - AlfCano/rk.survey.design: This plugin will generate and execute the R code needed to create a `survey.design` object based on your selections, and display a summary of the design object in the RKWard results window.
GitHub - AlfCano/rk.transpose.df: A simple transpose data.frame plug-in
GitHub - AlfCano/rk.aiken_v: An RKWard plugin to calculate Aiken's V and its score confidence intervals for content validity. Features tabular output, ggplot2 visualization, and a live plot preview.
GitHub - AlfCano/rk.shiny.plugins: Create a GUI for shiny plugins in RKWard
GitHub - AlfCano/rk.dplyr: RKWard plugin for dplyr table combinations.
GitHub - AlfCano/rk.stringr: Provides a user-friendly graphical interface for the powerful stringr package, bringing modern, consistent, and intuitive string manipulation directly into your RKWard workflow.
GitHub - AlfCano/rk.ggsurvey: A plugin package analyze complex survey designs with custom plugins and the 'ggsurvey' package.
GitHub - AlfCano/rk.cartographr: An RKWard plugin package for creating beautiful maps using the `cartographr` R package. This plugin provides a graphical user interface (GUI) to fetch data from OpenStreetMap and generate customizable map plots directly within RKWard.
GitHub - AlfCano/rk.questionr: A plugin package to analyze complex survey designs with custom plugins and the 'questionr' package.
GitHub - AlfCano/rk.lubridate: An RKWard plugin package for working with dates and times data using the 'lubridate' library.
GitHub - AlfCano/rk.dates: This package provides a single, powerful RKWard plugin designed to convert various numeric and character representations of dates and times into R's standard `POSIXct` (date-time) format. It simplifies the often-tricky process of handling date/time data imported from other statistical software or sources.
GitHub - AlfCano/rk.svyplot: This package provides an RKWard GUI front-end for the base graphics plotting functions included in the powerful **`survey`** package. It allows users to create survey-weighted plots, which can be more representative than standard plots, without writing R code.
GitHub - AlfCano/rk.names.labels: A plugin package to clean and create names and labels of variables of a data.frame or manipulate names in a list in the Rkward GUI.
GitHub - AlfCano/rk.class.lists: This package provides a suite of RKWard plugins designed to simplify the manipulation of R object classes and data structures. It offers a graphical interface for coercing objects (e.g., converting a matrix to a data frame), changing vector types (e.g., numeric to factor), and performing complex list operations (creating, appending, and extracting)
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