knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" ) options(cli.hyperlink = FALSE)
The tidyverse is a set of packages that work in harmony because they share common data representations and API design. The tidyverse package is designed to make it easy to install and load core packages from the tidyverse in a single command.
If you'd like to learn how to use the tidyverse effectively, the best place to start is R for Data Science (2e).
::: .pkgdown-release
# Install from CRAN install.packages("tidyverse")
:::
::: .pkgdown-devel
# Install the development version from GitHub # install.packages("pak") pak::pak("tidyverse/tidyverse")
:::
If you're compiling from source, you can run pak::pkg_system_requirements("tidyverse")
, to see the complete set of system packages needed on your machine.
library(tidyverse)
will load the core tidyverse packages:
You also get a condensed summary of conflicts with other packages you have loaded:
library(tidyverse)
You can see conflicts created later with tidyverse_conflicts()
:
library(MASS) tidyverse_conflicts()
And you can check that all tidyverse packages are up-to-date with tidyverse_update()
:
tidyverse_update() #> The following packages are out of date: #> * broom (0.4.0 -> 0.4.1) #> * DBI (0.4.1 -> 0.5) #> * Rcpp (0.12.6 -> 0.12.7) #> #> Start a clean R session then run: #> install.packages(c("broom", "DBI", "Rcpp"))
As well as the core tidyverse, installing this package also installs a selection of other packages that you're likely to use frequently, but probably not in every analysis. This includes packages for:
Working with specific types of vectors:
Importing other types of data:
Modelling
Please note that the tidyverse project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
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