Function reference • tidyr

Pivoting Pivoting changes the representation of a rectangular dataset, without changing the data inside of it. See `vignette("pivot")` for more details and examples.
`pivot_longer()`	Pivot data from wide to long
`pivot_wider()`	Pivot data from long to wide
Rectangling Rectangling turns deeply nested lists into tidy tibbles. See `vignette("rectangle")` for more details and examples.
`hoist()` `unnest_longer()` `unnest_wider()` `unnest_auto()`	Rectangle a nested list into a tidy tibble
Nesting Nesting uses alternative representation of grouped data where a group becomes a single row containing a nested data frame. See `vignette("nest")` for more details and examples.
`nest()` `unnest()`	Nest and unnest
Character vectors Multiple variables are sometimes pasted together into a single column, and these tools help you separate back out into individual columns.
`extract()`	Extract a character column into multiple columns using regular expression groups
`separate()`	Separate a character column into multiple columns with a regular expression or numeric locations
`separate_rows()`	Separate a collapsed column into multiple rows
`unite()`	Unite multiple columns into one by pasting strings together
Missing values Tools for converting between implicit (absent rows) and explicit (`NA`) missing values, and for handling explicit `NA`s.
`complete()`	Complete a data frame with missing combinations of data
`drop_na()`	Drop rows containing missing values
`expand()` `crossing()` `nesting()`	Expand data frame to include all possible combinations of values
`expand_grid()`	Create a tibble from all combinations of inputs
`fill()`	Fill in missing values with previous or next value
`full_seq()`	Create the full sequence of values in a vector
`replace_na()`	Replace NAs with specified values
Miscellanea
`chop()` `unchop()`	Chop and unchop
`pack()` `unpack()`	Pack and unpack
`uncount()`	"Uncount" a data frame
Data
`billboard`	Song rankings for Billboard top 100 in the year 2000
`construction`	Completed construction in the US in 2018
`fish_encounters`	Fish encounters
`relig_income`	Pew religion and income survey
`smiths`	Some data about the Smith family
`table1` `table2` `table3` `table4a` `table4b` `table5`	Example tabular representations
`us_rent_income`	US rent and income data
`who` `population`	World Health Organization TB data
`world_bank_pop`	Population data from the world bank
Superseded Functions that are still supported but no longer receive active development, as better solutions now exist.
`spread()`	Spread a key-value pair across multiple columns
`gather()`	Gather columns into key-value pairs
`nest_legacy()` `unnest_legacy()`	Legacy versions of `nest()` and `unnest()`

Reference

Pivoting

Rectangling

Nesting

Character vectors

Missing values

Miscellanea

Data

Superseded