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.
library(tidyverse) will load the core tidyverse packages:
You also get a condensed summary of conflicts with other packages you have loaded:
library(tidyverse) #> ── Attaching packages ───────────────────────────── tidyverse 184.108.40.20600 ── #> ✔ ggplot2 3.2.0 ✔ purrr 0.3.2 #> ✔ tibble 2.1.3 ✔ dplyr 0.8.3 #> ✔ tidyr 0.8.3 ✔ stringr 1.4.0 #> ✔ readr 1.3.1 ✔ forcats 0.4.0 #> ── Conflicts ───────────────────────────────────── tidyverse_conflicts() ── #> ✖ dplyr::filter() masks stats::filter() #> ✖ dplyr::lag() masks stats::lag()
You can see conflicts created later with
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()
And you can check that all tidyverse packages are up-to-date with
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: