Arranging Functions

Functions for arranging (sorting) rows. These are SciViews::R versions with standard evaluation and formula-based non-standard evaluation (ending with underscore _).

arrange_(
  .data = (.),
  ...,
  .by_group = FALSE,
  .locale = "C",
  .decreasing = FALSE
)

Arguments

.data

A data frame (data.frame, data.table or tibble's tbl_df). If not provided, the data-dot mechanism injects . as .data= automatically.

...

Either standard (quoted) column names of data. of formulas like ~col_name (formula-masking).

.by_group

Logical. If TRUE rows are first arranged by the grouping variables if any (applies only to grouped data frames). FALSE by default.

.locale

The locale to sort character vectors in. If NULL(default), use the "dplyr.legacy_locale" option (same one as dplyr::arrange()), and if not specified, it uses a "C" locale.

.decreasing

Sort in decreasing order (no, FALSE, by default)?

Value

A similar object as .data with all columns, all attributes and groups preserved, but row rearranged according to the specified order.

Details

For the way missing data are handled, see dplyr::arrange().

See also

dplyr::arrange()

Examples

library(svTidy)
data(mtcars, package = 'datasets')
mtcars <- data.trame::as.data.trame(mtcars)
# Standard evaluation (provide quoted names of the columns to sort)
# You cannot use desc(col) here, but must specify what you want in the
# .decreasing argument
arrange_(mtcars, 'cyl', 'disp', .decreasing = c(FALSE, TRUE))
#> # A data.trame: [32 × 11]
#>                 mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>             * <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> Merc 240D      24.4     4 147.     62  3.69  3.19  20       1     0     4     2
#> Merc 230       22.8     4 141.     95  3.92  3.15  22.9     1     0     4     2
#> Volvo 142E     21.4     4 121     109  4.11  2.78  18.6     1     1     4     2
#> Porsche 914-2  26       4 120.     91  4.43  2.14  16.7     0     1     5     2
#> Toyota Corona  21.5     4 120.     97  3.7   2.46  20.0     1     0     3     1
#> Datsun 710     22.8     4 108      93  3.85  2.32  18.6     1     1     4     1
#> Lotus Europa   30.4     4  95.1   113  3.77  1.51  16.9     1     1     5     2
#> Fiat X1-9      27.3     4  79      66  4.08  1.94  18.9     1     1     4     1
#> Fiat 128       32.4     4  78.7    66  4.08  2.2   19.5     1     1     4     1
#> Honda Civic    30.4     4  75.7    52  4.93  1.62  18.5     1     1     4     2
#> # ℹ 22 more rows
# With formula masking, you can use desc()
arrange_(mtcars, ~cyl, ~desc(disp))
#> # A data.trame: [32 × 11]
#>                 mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>             * <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> Merc 240D      24.4     4 147.     62  3.69  3.19  20       1     0     4     2
#> Merc 230       22.8     4 141.     95  3.92  3.15  22.9     1     0     4     2
#> Volvo 142E     21.4     4 121     109  4.11  2.78  18.6     1     1     4     2
#> Porsche 914-2  26       4 120.     91  4.43  2.14  16.7     0     1     5     2
#> Toyota Corona  21.5     4 120.     97  3.7   2.46  20.0     1     0     3     1
#> Datsun 710     22.8     4 108      93  3.85  2.32  18.6     1     1     4     1
#> Lotus Europa   30.4     4  95.1   113  3.77  1.51  16.9     1     1     5     2
#> Fiat X1-9      27.3     4  79      66  4.08  1.94  18.9     1     1     4     1
#> Fiat 128       32.4     4  78.7    66  4.08  2.2   19.5     1     1     4     1
#> Honda Civic    30.4     4  75.7    52  4.93  1.62  18.5     1     1     4     2
#> # ℹ 22 more rows