Menu
The Ultimate Guide to the readxl Package in R
Explore valuable documentation and insights to make the most of the readxl package in R. Get ready to unlock the full potential of the readxl package!
Learn R for Free with DataCamp
Master in-demand skills with DataCamp's interactive courses
Start Learning NowAs our partner, DataCamp may pay us a commission at no cost to you for purchases made through this link.
AI-powered R programming assistant
Have questions about the readxl package? Get quick and helpful answers from our cutting-edge AI-powered assistant.
Advance Your Career with Udacity
Take your data and AI skills to the next level with industry-recognized Nanodegree programs
Explore CoursesAs our partner, Udacity may pay us a commission at no cost to you for purchases made through this link.
What is the readxl package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The readxl package provides tools to read Excel files (.xls and .xlsx) into R. It simplifies the process of importing Excel data, catering to a wide range of users including data analysts, statisticians, and scientists.
- Title: Read Excel Files
- Description: Import excel files into R. Supports '.xls' via the embedded 'libxls' C library and '.xlsx' via the embedded 'RapidXML' C++ library . Works on Windows, Mac and Linux without external dependencies.
- Author: Hadley Wickham [aut] (), Jennifer Bryan [aut, cre] (), Posit, PBC [cph, fnd] (Copyright holder of all R code and all C/C++ code without explicit copyright attribution), Marcin Kalicinski [ctb, cph] (Author of included RapidXML code), Komarov Valery [ctb, cph] (Author of included libxls code), Christophe Leitienne [ctb, cph] (Author of included libxls code), Bob Colbert [ctb, cph] (Author of included libxls code), David Hoerl [ctb, cph] (Author of included libxls code), Evan Miller [ctb, cph] (Author of included libxls code)
- Maintainer: Jennifer Bryan
How to install the readxl package?
In this section, we’ll walk you through the process of installing and loading the readxl package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.
Upskill Your Data Science Team with O'Reilly
Access expert-led courses and resources for R programming and beyond
Explore O'Reilly's LibraryAs our partner, O'Reilly may pay us a commission at no cost to you for purchases made through this link.
What package information should you know?
In this section, we’ll go over the technical aspects of the readxl 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 readxl 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 readxl 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 readxl package, visit our database of R package citations.
Technical details
- License type: MIT + file LICENSE. 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 readxl package has compilation requirements.
- Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The readxl package has the following required dependencies: R (>= 3.6).
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The readxl package has the following suggested dependencies: covr, knitr, rmarkdown, testthat (>= 3.1.6), withr.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The readxl package uses the following external sources: cpp11 (>= 0.4.0), progress.
- Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The readxl package has the following imported packages: cellranger, tibble (>= 2.0.1), utils.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The readxl package has no enhancements.
How to get help with the readxl package?
In this section, we’ll discuss a variety of available resources for getting help with the readxl package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("readxl") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
-
Package website: The readxl package has a dedicated website. You can visit: https://readxl.tidyverse.org, https://github.com/tidyverse/readxl.
- Developer support: You can email Jennifer Bryan . For contact information, visit our R community directory.
Additional resources
- AI tools: Use AI programming tools like DataLab to promptly address your questions. (Please note that we may earn a commission if you purchase through this link. By trying DataLab, you help sustain our platform. Thank you for your support!)
- Online courses: Try our handpicked collection of R programming courses designed to boost your proficiency in R programming.
- Books: Explore our curated selection of R programming books tailored to help you master R programming.
- 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.
Share the Post: