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tidyverse

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![CRAN
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Overview

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).

Installation

r
# Install from CRAN
install.packages("pak")

If you have any problems installing tidyverse, we recommend trying with
pak since it is likely to help diagnose the
problem:

r
# install.packages("pak")
pak::pak("tidyverse")

r
# 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.

Usage

library(tidyverse) will load the core tidyverse packages:

• ggplot2, for data visualisation.
• dplyr, for data manipulation.
• tidyr, for data tidying.
• readr, for data import.
• purrr, for functional programming.
• tibble, for tibbles, a modern

re-imagining of data frames.

• stringr, for strings.
• forcats, for factors.
• lubridate, for date/times.

You also get a condensed summary of conflicts with other packages you have loaded:

r
library(tidyverse)
#> ── Attaching core tidyverse packages ─────────────────── tidyverse 2.0.0.9000 ──
#> ✔ dplyr     1.1.4     ✔ readr     2.1.5
#> ✔ forcats   1.0.0     ✔ stringr   1.5.1
#> ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
#> ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
#> ✔ purrr     1.0.2     
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ℹ Use the conflicted package () to force all conflicts to become errors

You can see conflicts created later with tidyverse_conflicts():

r
library(MASS)
#> 
#> Attaching package: 'MASS'
#> The following object is masked from 'package:dplyr':
#> 
#>     select
tidyverse_conflicts()
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ✖ MASS::select()  masks dplyr::select()
#> ℹ Use the conflicted package () to force all conflicts to become errors

And you can check that all tidyverse packages are up-to-date with
tidyverse_update():

r
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"))

Packages

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:

- hms, for times.

• Importing other types of data:

- haven, for SPSS, SAS and Stata files. - httr, for web apis. - jsonlite for JSON. - readxl, for .xls and .xlsx files. - rvest, for web scraping. - xml2, for XML.

• Modelling

- broom, for turning models into tidy data

Code of Conduct

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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