./math/R-tidyr, Easily tidy data with spread() and gather() functions

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Branch: CURRENT, Version: 1.2.1, Package name: R-tidyr-1.2.1, Maintainer: pkgsrc-users

An evolution of 'reshape2'. It's designed specifically for data
tidying (not general reshaping or aggregating) and works well with
'dplyr' data pipelines.

Required to run:
[math/R] [devel/R-Rcpp] [textproc/R-stringi] [devel/R-magrittr] [devel/R-rlang] [math/R-tibble] [devel/R-glue] [devel/R-purrr] [devel/R-tidyselect]

Required to build:

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Version history: (Expand)

CVS history: (Expand)

   2022-12-18 15:17:14 by Makoto Fujiwara | Files touched by this commit (2)
Log message:
(math/R-tidyr) Updated 1.2.0 to 1.2.1

# tidyr 1.2.1

* Hot patch release to resolve R CMD check failures.
   2022-05-01 18:10:16 by Makoto Fujiwara | Files touched by this commit (2) | Package updated
Log message:
(math/R-tidyr) Updated 1.1.3 to 1.2.0

# tidyr 1.2.0

## Pivoting

* `pivot_wider()` gains new `names_expand` and `id_expand` arguments for turning
  implicit missing factor levels and variable combinations into explicit ones.
  This is similar to the `drop` argument from `spread()` (#770).

* `pivot_wider()` gains a new `names_vary` argument for controlling the
  ordering when combining `names_from` values with `values_from` column names

* `pivot_wider()` gains a new `unused_fn` argument for controlling how to
  summarize unused columns that aren't involved in the pivoting process (#990,
  thanks to @mgirlich for an initial implementation).

* `pivot_longer()`'s `names_transform` and `values_transform` arguments now
  accept a single function which will be applied to all of the columns
  (#1284, thanks to @smingerson for an initial implementation).

* `pivot_longer()`'s `names_ptypes` and `values_ptypes` arguments now
  accept a single empty ptype which will be applied to all of the columns

## Nesting

* `unnest()` and `unchop()`'s `ptype` argument now accepts a single empty
  ptype which will be applied to all `cols` (#1284).

* `unpack()` now silently skips over any non-data frame columns specified by
  `cols`. This matches the existing behavior of `unchop()` and `unnest()`

## Rectangling

* `unnest_wider()` and `unnest_longer()` can now unnest multiple columns at
  once (#740).

* `unnest_longer()`'s `indices_to` and `values_to` arguments now accept
  a glue specification, which is useful when unnesting multiple columns.

* For `hoist()`, `unnest_longer()`, and `unnest_wider()`, if a `ptype` is
  supplied, but that column can't be simplified, the result will be a list-of
  column where each element has type `ptype` (#998).

* `unnest_wider()` gains a new `strict` argument which controls whether or not
  strict vctrs typing rules should be applied. It defaults to `FALSE` for
  backwards compatibility, and because it is often more useful to be lax
  when unnesting JSON, which doesn't always map one-to-one with R's types

* `hoist()`, `unnest_longer()`, and `unnest_wider()`'s `simplify` argument now
  accepts a named list of `TRUE` or `FALSE` to control simplification on a per
  column basis (#995).

* `hoist()`, `unnest_longer()`, and `unnest_wider()`'s `transform` argument now
  accepts a single function which will be applied to all components (#1284).

* `hoist()`, `unnest_longer()`, and `unnest_wider()`'s `ptype` argument now
  accepts a single empty ptype which will be applied to all components (#1284).

## Grids

* `complete()` gains a new `explicit` argument for limiting `fill` to only
  implicit missing values. This is useful if you don't want to fill in
  pre-existing missing values (#1270).

* `complete()` gains a grouped data frame method. This generates a more correct
  completed data frame when groups are involved (#396, #966).

* `complete()` and `expand()` no longer allow you to complete or expand on a
  grouping column. This was never well-defined since completion/expansion on a
  grouped data frame happens "within" each group and otherwise has the
  potential to produce erroneous results (#1299).

## Missing values

* `drop_na()`, `replace_na()`, and `fill()` have been updated to utilize vctrs.
  This means that you can use these functions on a wider variety of column
  types, including lubridate's Period types (#1094), data frame columns, and
  the [rcrd](https://vctrs.r-lib.org/reference/new_rcrd.html) type from vctrs.

* `replace_na()` no longer allows the type of `data` to change when the
  replacement is applied. `replace` will now always be cast to the type of
  `data` before the replacement is made. For example, this means that using a
  replacement value of `1.5` on an integer column is no longer allowed.
  Similarly, replacing missing values in a list-column must now be done with
  `list("foo")` rather than just `"foo"`.

* `replace_na()` no longer replaces empty atomic elements in list-columns
  (like `integer(0)`). The only value that is replaced in a list-column is
  `NULL` (#1168).

* `drop_na()` no longer drops empty atomic elements from list-columns
  (like `integer(0)`). The only value that is dropped in a list-column is
  `NULL` (#1228).

## Bug fixes and minor improvements

### General

* @mgirlich is now a tidyr author in recognition of his significant and
  sustained contributions.

* All lazyeval variants of tidyr verbs have been soft-deprecated. Expect them
  to move to the defunct stage in the next minor release of tidyr (#1294).

* `any_of()` and `all_of()` from tidyselect are now re-exported (#1217).

* dplyr >= 1.0.0 is now required.

### Pivoting

* `pivot_wider()` now gives better advice about how to identify duplicates when
  values are not uniquely identified (#1113).

* `pivot_wider()` now throws a more informative error when `values_fn` doesn't
  result in a single summary value (#1238).

* `pivot_wider()` and `pivot_longer()` now generate more informative
  errors related to name repair (#987).

* `pivot_wider()` now works correctly when `values_fill` is a data frame.

* `pivot_wider()` no longer accidentally retains `values_from` when pivoting
  a zero row data frame (#1249).

* `pivot_wider()` now correctly handles the case where an id column name
  collides with a value from `names_from` (#1107).

* `pivot_wider()` and `pivot_longer()` now both check that the spec columns
  `.name` and `.value` are character vectors. Additionally, the `.name`
  column must be unique (#1107).

* `pivot_wider()`'s `names_from` and `values_from` arguments are now
  required if their default values of `name` and `value` don't correspond to
  columns in `data`. Additionally, they must identify at least 1 column
  in `data` (#1240).

* `pivot_wider()`'s `values_fn` argument now correctly allows anonymous
  functions (#1114).

* `pivot_wider_spec()` now works correctly with a 0-row data frame and a `spec`
  that doesn't identify any rows (#1250, #1252).

* `pivot_longer()`'s `names_ptypes` argument is now applied after
  `names_transform` for consistency with the rectangling functions
  (i.e. `hoist()`) (#1233).

* `check_pivot_spec()` is a new developer facing function for validating a pivot
  `spec` argument. This is only useful if you are extending `pivot_longer()` or
  `pivot_wider()` with new S3 methods (#1087).

### Nesting

* The `nest()` generic now avoids computing on `.data`, making it more
  compatible with lazy tibbles (#1134).

* The `.names_sep` argument of the data.frame method for `nest()` is now
  actually used (#1174).

* `unnest()`'s `ptype` argument now works as expected (#1158).

* `unpack()` no longer drops empty columns specified through `cols` (#1191).

* `unpack()` now works correctly with data frame columns containing 1 row but
  0 columns (#1189).

* `chop()` now works correctly with data frames with 0 rows (#1206).

* `chop()`'s `cols` argument is no longer optional. This matches the
  behavior of `cols` seen elsewhere in tidyr (#1205).

* `unchop()` now respects `ptype` when unnesting a non-list column (#1211).

### Rectangling

* `hoist()` no longer accidentally removes elements that have duplicated names

### Grids

* The grouped data frame methods for `complete()` and `expand()` now move the
  group columns to the front of the result (in addition to the columns you
  completed on or expanded, which were already moved to the front). This should
  make more intuitive sense, as you are completing or expanding \ 
"within" each
  group, so the group columns should be the first thing you see (#1289).

* `complete()` now applies `fill` even when no columns to complete are
  specified (#1272).

* `expand()`, `crossing()`, and `nesting()` now correctly retain `NA` values of
  factors (#1275).

* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now silently
  apply name repair to automatically named inputs. This avoids a number of
  issues resulting from duplicate truncated names
  (#1116, #1221, #1092, #1037, #992).

* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now allow
  columns from unnamed data frames to be used in expressions after that
  data frame was specified, like `expand_grid(tibble(x = 1), y = x)`. This
  is more consistent with how `tibble()` behaves.

* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now work
  correctly with data frames containing 0 columns but >0 rows (#1189).

* `expand_grid()`, `expand()`, `nesting()`, and `crossing()` now return a 1
  row data frame when no inputs are supplied, which is more consistent with
  `prod() == 1L` and the idea that computations involving the number of
  combinations computed from an empty set should return 1 (#1258).

### Missing values

* `drop_na()` no longer drops missing values from all columns when a tidyselect
  expression that results in 0 columns being selected is used (#1227).

* `fill()` now treats `NaN` like any other missing value (#982).

# tidyr 1.1.4

* `expand_grid()` is now about twice as fast and `pivot_wider()` is a bit faster
  (@mgirlich, #1130).

* `unchop()` is now much faster, which propagates through to various functions,
  such as `unnest()`, `unnest_longer()`, `unnest_wider()`, and
  `separate_rows()` (@mgirlich, @DavisVaughan, #1127).

* `unnest()` is now much faster (@mgirlich, @DavisVaughan, #1127).

* `unnest()` no longer allows unnesting a list-col containing a mix of vector
  and data frame elements. Previously, this only worked by accident, and is
  considered an off-label usage of `unnest()` that has now become an error.
   2021-10-26 12:56:13 by Nia Alarie | Files touched by this commit (458)
Log message:
math: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes
   2021-10-07 16:28:36 by Nia Alarie | Files touched by this commit (458)
Log message:
math: Remove SHA1 hashes for distfiles
   2021-09-18 16:01:44 by Makoto Fujiwara | Files touched by this commit (2) | Package updated
Log message:
(math/R-tidyr) Updated 1.0.2 to 1.1.3

# tidyr 1.1.3

* tidyr verbs no longer have "default" methods for lazyeval fallbacks. This
  means that you'll get clearer error messages (#1036).

* `uncount()` error for non-integer weights and gives a clearer error message
  for negative weights (@mgirlich, #1069).

* You can once again unnest dates (#1021, #1089).

* `pivot_wider()` works with data.table and empty key variables (@mgirlich, #1066).

* `separate_rows()` works for factor columns (@mgirlich, #1058).

# tidyr 1.1.2

* `separate_rows()` returns to 1.1.0 behaviour for empty strings
  (@rjpatm, #1014).

# tidyr 1.1.1

* New tidyr logo!

* stringi dependency has been removed; this was a substantial dependency that
  make tidyr hard to compile in resource constrained environments
  (@rjpat, #936).

* Replace Rcpp with cpp11. See \ 
  for reasons why.

# tidyr 1.1.0

## General features

* `pivot_longer()`, `hoist()`, `unnest_wider()`, and `unnest_longer()` gain
  new `transform` arguments; these allow you to transform values "in \ 
  They are partly needed because vctrs coercion rules have become stricter,
  but they give you greater flexibility than was available previously (#921).

* Arguments that use tidy selection syntax are now clearly documented and
  have been updated to use tidyselect 1.1.0 (#872).

## Pivoting improvements

* Both `pivot_wider()` and `pivot_longer()` are considerably more performant,
  thanks largely to improvements in the underlying vctrs code
  (#790, @DavisVaughan).

* `pivot_longer()` now supports `names_to = character()` which prevents the
  name column from being created (#961).

    df <- tibble(id = 1:3, x_1 = 1:3, x_2 = 4:6)
    df %>% pivot_longer(-id, names_to = character())

* `pivot_longer()` no longer creates a `.copy` variable in the presence of
  duplicate column names. This makes it more consistent with the handling
  of non-unique specs.

* `pivot_longer()` automatically disambiguates non-unique ouputs, which can
  occur when the input variables include some additional component that you
  don't care about and want to discard (#792, #793).

    df <- tibble(id = 1:3, x_1 = 1:3, x_2 = 4:6)
    df %>% pivot_longer(-id, names_pattern = "(.)_.")
    df %>% pivot_longer(-id, names_sep = "_", names_to = \ 
c("name", NA))
    df %>% pivot_longer(-id, names_sep = "_", names_to = \ 
c(".value", NA))

* `pivot_wider()` gains a `names_sort` argument which allows you to sort
  column names in order. The default, `FALSE`, orders columms by their
  first appearance (#839). In a future version, I'll consider changing the
  default to `TRUE`.

* `pivot_wider()` gains a `names_glue` argument that allows you to construct
  output column names with a glue specification.

* `pivot_wider()` arguments `values_fn` and `values_fill` can now be single
  values; you now only need to use a named list if you want to use different
  values for different value columns (#739, #746). They also get improved
  errors if they're not of the expected type.

## Rectangling

* `hoist()` now automatically names pluckers that are a single string (#837).
  It error if you use duplicated column names (@mgirlich, #834), and now uses
  `rlang::list2()` behind the scenes (which means that you can now use `!!!`
  and `:=`) (#801).

* `unnest_longer()`, `unnest_wider()`, and `hoist()` do a better job
  simplifying list-cols. They no longer add unneeded `unspecified()` when
  the result is still a list (#806), and work when the list contains
  non-vectors (#810, #848).

* `unnest_wider(names_sep = "")` now provides default names for \ 
unnamed inputs,
  suppressing the many previous name repair messages (#742).

## Nesting

* `pack()` and `nest()` gains a `.names_sep` argument allows you to strip outer
  names from inner names, in symmetrical way to how the same argument to
  `unpack()` and `unnest()` combines inner and outer names (#795, #797).

* `unnest_wider()` and `unnest_longer()` can now unnest `list_of` columns. This
  is important for unnesting columns created from `nest()` and with
  `pivot_wider()`, which will create `list_of` columns if the id columns are
  non-unique (#741).

## Bug fixes and minor improvements

* `chop()` now creates list-columns of class `vctrs::list_of()`. This helps
  keep track of the type in case the chopped data frame is empty, allowing
  `unchop()` to reconstitute a data frame with the correct number and types
  of column even when there are no observations.

* `drop_na()` now preserves attributes of unclassed vectors (#905).

* `expand()`, `expand_grid()`, `crossing()`, and `nesting()` once again
  evaluate their inputs iteratively, so you can refer to freshly created
  columns, e.g. `crossing(x = seq(-2, 2), y = x)` (#820).

* `expand()`, `expand_grid()`, `crossing()`, and `nesting()` gain a
  `.name_repair` giving you control over their name repair strategy
  (@jeffreypullin, #798).

* `extract()` lets you use `NA` in `into`, as documented (#793).

* `extract()`, `separate()`, `hoist()`, `unnest_longer()`, and `unnest_wider()`
  give a better error message if `col` is missing (#805).

* `pack()`'s first argument is now `.data` instead of `data` (#759).

* `pivot_longer()` now errors if `values_to` is not a length-1 character vector

* `pivot_longer()` and `pivot_wider()` are now generic so implementations
  can be provided for objects other than data frames (#800).

* `pivot_wider()` can now pivot data frame columns (#926)

* `unite(na.rm = TRUE)` now works for all types of variable, not just character
  vectors (#765).

* `unnest_wider()` gives a better error message if you attempt to unnest
  multiple columns (#740).

* `unnest_auto()` works when the input data contains a column called `col`
   2020-07-31 23:49:29 by Brook Milligan | Files touched by this commit (2) | Package updated
Log message:
R-tidyr: update from 0.8.3 to 1.0.2.

Many changes are identified for the update to 1.0.0; see News.md for

Apparently, these include some breaking changes.  See
`vignette("in-packages")` for a detailed transition guide.