R: Nest and un-nest an 'ir' object

nest {ir}

R Documentation

Nest and un-nest an `ir` object

Description

Nest and un-nest an ir object

Usage

nest.ir(.data, ..., .names_sep = NULL, .key = deprecated())

unnest.ir(
  data,
  cols,
  ...,
  keep_empty = FALSE,
  ptype = NULL,
  names_sep = NULL,
  names_repair = "check_unique",
  .drop = deprecated(),
  .id = deprecated(),
  .sep = deprecated(),
  .preserve = deprecated()
)

Arguments

`.data`	An object of class `ir`.
`...`	<`tidy-select`> Columns to nest, specified using name-variable pairs of the form `new_col = c(col1, col2, col3)`. The right hand side can be any valid tidy select expression. : previously you could write `df %>% nest(x, y, z)` and `df %>% unnest(x, y, z)`. Convert to `df %>% nest(data = c(x, y, z))`. and `df %>% unnest(c(x, y, z))`. If you previously created new variable in `unnest()` you'll now need to do it explicitly with `mutate()`. Convert `df %>% unnest(y = fun(x, y, z))` to `df %>% mutate(y = fun(x, y, z)) %>% unnest(y)`.
`.key`	: No longer needed because of the new `new_col = c(col1, col2, col3)` syntax.
`data`	A data frame.
`cols`	<`tidy-select`> Columns to unnest. If you `unnest()` multiple columns, parallel entries must be of compatible sizes, i.e. they're either equal or length 1 (following the standard tidyverse recycling rules).
`keep_empty`	By default, you get one row of output for each element of the list your unchopping/unnesting. This means that if there's a size-0 element (like `NULL` or an empty data frame), that entire row will be dropped from the output. If you want to preserve all rows, use `keep_empty = TRUE` to replace size-0 elements with a single row of missing values.
`ptype`	Optionally, a named list of column name-prototype pairs to coerce `cols` to, overriding the default that will be guessed from combining the individual values. Alternatively, a single empty ptype can be supplied, which will be applied to all `cols`.
`names_sep`, `.names_sep`	If `NULL`, the default, the names will be left as is. In `nest()`, inner names will come from the former outer names; in `unnest()`, the new outer names will come from the inner names. If a string, the inner and outer names will be used together. In `unnest()`, the names of the new outer columns will be formed by pasting together the outer and the inner column names, separated by `names_sep`. In `nest()`, the new inner names will have the outer names + `names_sep` automatically stripped. This makes `names_sep` roughly symmetric between nesting and unnesting.
`names_repair`	Used to check that output data frame has valid names. Must be one of the following options: "minimal": no name repair or checks, beyond basic existence, "unique": make sure names are unique and not empty, "check_unique": (the default), no name repair, but check they are unique, "universal": make the names unique and syntactic a function: apply custom name repair. tidyr_legacy: use the name repair from tidyr 0.8. a formula: a purrr-style anonymous function (see `rlang::as_function()`) See `vctrs::vec_as_names()` for more details on these terms and the strategies used to enforce them.
`.drop`, `.preserve`	: all list-columns are now preserved; If there are any that you don't want in the output use `select()` to remove them prior to unnesting.
`.id`	: convert `df %>% unnest(x, .id = "id")` to `⁠df %>% mutate(id = names(x)) %>% unnest(x))⁠`.
`.sep`	: use `names_sep` instead.

Value

.data with nested or unnested columns. If the spectra column is dropped or invalidated (see ir_new_ir()), the ir class is dropped, else the object is of class ir.

Source

tidyr::nest()

Examples

## nest
ir_sample_data %>%
  tidyr::nest(
    contents = c(holocellulose, klason_lignin)
  )


## unnest
ir_sample_data %>%
  tidyr::nest(
    contents = c(holocellulose, klason_lignin)
  ) %>%
  tidyr::unnest("contents")

[Package ir version 0.2.1 Index]

Nest and un-nest an ir object