Installation and use
-
Install all the packages in the tidyverse by running
install.packages("tidyverse")
. -
Run
library(tidyverse)
to load the core tidyverse and make it available in your current R session.
Learn more about the tidyverse package at https://tidyverse.tidyverse.org.
Core tidyverse
The core tidyverse includes the packages that you’re likely to use in everyday data analyses. As of tidyverse 1.3.0, the following packages are included in the core tidyverse:
zscorer
Anthropometric z-score calculator
nipnTK
National Information Platforms for Nutrition (NiPN) data quality toolkit
anthrocheckr
An implementation of anthropometric measurement standardisation Tests in R
nutricheckr
Tools for nutrition assessment and analysis
intergrowth
An R implementation of the INTERGROWTH-21st standards and tools
nutricea
Nutrition cost-effectiveness analysis (CEA) in R
nutribudgetr
An implementation of SPRING's nutrition budget analysis tool in R
cmam
An R Companion to Community-based Management of Acute Malnutrition
The tidyverse also includes many other packages with more specialised usage. They are not loaded automatically with library(tidyverse)
, so you’ll need to load each one with its own call to library()
.
Import
As well as readr, for reading flat files, the tidyverse package installs a number of other packages for reading data:
-
DBI for relational databases. (Maintained by Kirill Müller.) You’ll need to pair DBI with a database specific backends like RSQLite, RMariaDB, RPostgres, or odbc. Learn more at https://db.rstudio.com.
-
haven for SPSS, Stata, and SAS data.
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httr for web APIs.
-
readxl for
.xls
and.xlsx
sheets. -
rvest for web scraping.
-
jsonlite for JSON. (Maintained by Jeroen Ooms.)
-
xml2 for XML.
Wrangle
In addition to tidyr, and dplyr, there are five packages (including stringr and forcats) which are designed to work with specific types of data:
- lubridate for dates and date-times.
- hms for time-of-day values.
- blob for storing blob (binary) data.
Program
In addition to purrr, which provides very consistent and natural methods for iterating on R objects, there are two additional tidyverse packages that help with general programming challenges:
-
magrittr provides the pipe,
%>%
used throughout the tidyverse. It also provide a number of more specialised piping operators (like%$%
and%<>%
) that can be useful in other places. -
glue provides an alternative to
paste()
that makes it easier to combine data and strings.
Model
Modeling with the tidyverse uses the collection of tidymodels packages, which largely replace the modelr package used in R4DS. These packages provide a comprehensive foundation for creating and using models of all types. Visit the Getting Started guide or, for more detailed examples, go straight to the Learn page.
Get help
If you’re asking for R help, reporting a bug, or requesting a new feature, you’re more likely to succeed if you include a good reproducible example, which is precisely what the reprex package is meant for. You can learn more about reprex, along with other tips on how to help others help you in the help section.