The Ultimate Guide to the pivottabler Package in R
Explore valuable documentation and insights to make the most of the pivottabler package in R. Get ready to unlock the full potential of the pivottabler package!
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What is the pivottabler package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The pivottabler package is a powerful tool in R for creating pivot tables. It allows users to easily summarize and explore data, providing a high level of customization to suit various analysis needs.
- Title: Create Pivot Tables
- Description: Create regular pivot tables with just a few lines of R. More complex pivot tables can also be created, e.g. pivot tables with irregular layouts, multiple calculations and/or derived calculations based on multiple data frames. Pivot tables are constructed using R only and can be written to a range of output formats (plain text, 'HTML', 'Latex' and 'Excel'), including with styling/formatting.
- Author: Christopher Bailiss [aut, cre]
- Maintainer: Christopher Bailiss
How to install the pivottabler package?
In this section, we’ll walk you through the process of installing and loading the pivottabler 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 pivottabler 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 pivottabler 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 pivottabler 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 pivottabler 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 pivottabler 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 pivottabler package has the following required dependencies: R (>= 3.3.0).
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The pivottabler package has the following suggested dependencies: ggplot2 (>= 2.2.0), jsonlite (>= 1.1), lubridate (>= 1.5.0), listviewer (>= 1.4.0), openxlsx (>= 4.0.17), basictabler (>= 1.0.2), shiny, knitr, rmarkdown, testthat.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The pivottabler 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 pivottabler package has the following imported packages: R6 (>= 2.2.0), dplyr (>= 0.5.0), data.table (>= 1.10.0), htmltools (>= 0.3.5), htmlwidgets (>= 0.8).
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The pivottabler package has no enhancements.
How to get help with the pivottabler package?
In this section, we’ll discuss a variety of available resources for getting help with the pivottabler package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("pivottabler") 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 pivottabler package has a dedicated website. You can visit: http://www.pivottabler.org.uk/, https://github.com/cbailiss/pivottabler.
- Developer support: You can email Christopher Bailiss . For contact information, visit our R community directory.
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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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