nest: Nest repeated values in a list-variable.

Description Usage Arguments Rules for selection See Also Examples

View source: R/nest.R


There are many possible ways one could choose to nest columns inside a data frame. nest() creates a list of data frames containing all the nested variables: this seems to be the most useful form in practice.


nest(data, ..., .key = "data")



A data frame.


A selection of columns. If empty, all variables are selected. You can supply bare variable names, select all variables between x and z with x:z, exclude y with -y. For more options, see the dplyr::select() documentation. See also the section on selection rules below.


The name of the new column, as a string or symbol.

This argument is passed by expression and supports quasiquotation (you can unquote strings and symbols). The name is captured from the expression with rlang::ensym() (note that this kind of interface where symbols do not represent actual objects is now discouraged in the tidyverse; we support it here for backward compatibility).

Rules for selection

Arguments for selecting columns are passed to tidyselect::vars_select() and are treated specially. Unlike other verbs, selecting functions make a strict distinction between data expressions and context expressions.

For instance, col1:col3 is a data expression that refers to data columns, while seq(start, end) is a context expression that refers to objects from the contexts.

If you really need to refer to contextual objects from a data expression, you can unquote them with the tidy eval operator !!. This operator evaluates its argument in the context and inlines the result in the surrounding function call. For instance, c(x, !! x) selects the x column within the data frame and the column referred to by the object x defined in the context (which can contain either a column name as string or a column position).

See Also

unnest() for the inverse operation.


as_tibble(iris) %>% nest(-Species)
as_tibble(chickwts) %>% nest(weight)

if (require("gapminder")) {
  gapminder %>%
    group_by(country, continent) %>%

  gapminder %>%
    nest(-country, -continent)

Example output

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

# A tibble: 3 x 2
     Species              data
      <fctr>            <list>
1     setosa <tibble [50 x 4]>
2 versicolor <tibble [50 x 4]>
3  virginica <tibble [50 x 4]>
# A tibble: 6 x 2
       feed              data
     <fctr>            <list>
1 horsebean <tibble [10 x 1]>
2   linseed <tibble [12 x 1]>
3   soybean <tibble [14 x 1]>
4 sunflower <tibble [12 x 1]>
5  meatmeal <tibble [11 x 1]>
6    casein <tibble [12 x 1]>
Loading required package: gapminder
Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called 'gapminder'

tidyr documentation built on Oct. 29, 2018, 1:04 a.m.