The Ultimate Guide to the shinypivottabler Package in R
Explore valuable documentation and insights to make the most of the shinypivottabler package in R. Get ready to unlock the full potential of the shinypivottabler package!
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What is the shinypivottabler package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The shinypivottabler package allows developers to create pivot tables within shiny applications. It offers a highly customizable and interactive interface that enables users to summarize and analyze data effectively.
- Title: Shiny Module to Create Pivot Tables
- Description: Shiny Module to create, visualize, customize and export Excel-like pivot table.
- Author: Benoit Thieurmel [aut, cre], Thibaut Dubois [aut]
- Maintainer: Benoit Thieurmel
How to install the shinypivottabler package?
In this section, we’ll walk you through the process of installing and loading the shinypivottabler package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.
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What package information should you know?
In this section, we’ll go over the technical aspects of the shinypivottabler package.
Key features
- Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify built-in datasets. To identify the datasets for the shinypivottabler package, visit our database of R datasets.
- Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes for the shinypivottabler package, you can visit our visit our database of R vignettes.
- Citation: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find citation information for the shinypivottabler package, visit our database of R package citations.
Technical details
- License type: GPL-3. For license details, visit the Open Source Initiative website.
- Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The shinypivottabler package does not have compilation requirements.
- Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The shinypivottabler package has the following required dependencies: R (>= 3.4).
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The shinypivottabler package has no suggested dependencies.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The shinypivottabler package does not use any external sources.
- Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The shinypivottabler package has the following imported packages: pivottabler (>= 1.5.0), shiny, openxlsx, colourpicker, htmltools.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The shinypivottabler package has no enhancements.
How to get help with the shinypivottabler package?
In this section, we’ll discuss a variety of available resources for getting help with the shinypivottabler package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("shinypivottabler") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
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Package website: The shinypivottabler package does not have a dedicated website.
- Developer support: You can email Benoit Thieurmel . For contact information, visit our R community directory.
Additional resources
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- Online courses: Try our handpicked collection of R programming courses designed to boost your proficiency in R programming.
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- Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.
Other package guides
Explore our comprehensive guides for other R packages. These guides are valuable resources for accessing a wide range of information, making it easier to navigate R documentation in one place.
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