Sorts the rows of a dataframe based on one or more columns using alphanumeric sorting order. Allows for specifying ascending or descending order for each sorting column individually.
Usage
arrange_alphanum(
data = NULL,
...,
desc = FALSE,
na_last = TRUE,
blank_last = FALSE,
scientific = TRUE
)Arguments
- data
A dataframe or tibble to be sorted.
- ...
Unquoted names of the columns to sort by (e.g., v1, v2, etc.) Sorting is done sequentially based on the order of columns provided.
- desc
Logical value or vector. If a single
TRUE, sorts all specified columns in descending alphanumeric order. If a singleFALSE(default), sorts all in ascending order. If a logical vector, its length must match the number of columns specified in..., determining the sort order for each column respectively (e.g.,c(FALSE, TRUE)for ascending first column, descending second).NAvalues indescare treated asFALSE(ascending). Columns must be character, numeric, or factor types for sorting.- na_last
for controlling the treatment of
NAvalues. IfTRUE, missing values in the data are put last; ifFALSE, they are put first; ifNA, they are removed. See gtools::mixedsort for more details.- blank_last
for controlling the treatment of blank values. If
TRUE, blank values in the data are put last; ifFALSE, they are put first; ifNA, they are removed. See gtools::mixedsort for more details.- scientific
logical. Should exponential notation be allowed for numeric values. See gtools::mixedsort for more details.
Note
The arrange_alphanum function sorts dataframe rows alphanumerically,
handling mixed numeric and character strings correctly (e.g., "A1", "A10",
"A2" as "A1", "A2", "A10"), whereas dplyr::arrange uses standard
lexicographic sorting, which may order them incorrectly (e.g., "A1", "A10",
"A2").
Examples
# increase the number of printed rows
options(pillar.print_max = 40)
load_packages(dplyr, tidyr, tibble)
# create a sample dataframe
set.seed(100)
(df <- tidyr::expand_grid(
v1 = c("A1", "A2", "A10", "A010", "A25"),
v2 = c("P1", "P2"), v3 = c(10, 5, 1, 15)) %>%
dplyr::slice_sample(n = 40))
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A2 P1 5
#> 2 A25 P2 5
#> 3 A010 P1 10
#> 4 A2 P2 5
#> 5 A10 P2 1
#> 6 A10 P2 5
#> 7 A1 P2 5
#> 8 A1 P1 15
#> 9 A25 P1 15
#> 10 A25 P1 5
#> 11 A1 P1 5
#> 12 A1 P2 1
#> 13 A010 P2 10
#> 14 A010 P2 15
#> 15 A2 P1 1
#> 16 A10 P2 15
#> 17 A10 P1 5
#> 18 A2 P1 15
#> 19 A1 P1 1
#> 20 A10 P1 1
#> 21 A1 P2 15
#> 22 A25 P2 1
#> 23 A010 P2 5
#> 24 A25 P1 10
#> 25 A10 P1 10
#> 26 A25 P2 10
#> 27 A2 P2 15
#> 28 A1 P2 10
#> 29 A010 P1 5
#> 30 A010 P1 15
#> 31 A2 P1 10
#> 32 A2 P2 1
#> 33 A10 P2 10
#> 34 A010 P2 1
#> 35 A2 P2 10
#> 36 A010 P1 1
#> 37 A10 P1 15
#> 38 A25 P2 15
#> 39 A1 P1 10
#> 40 A25 P1 1
# sort by v1 (ascending)
# arrange function does not sort alphanumerically
dplyr::arrange(df, v1)
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A010 P1 10
#> 2 A010 P2 10
#> 3 A010 P2 15
#> 4 A010 P2 5
#> 5 A010 P1 5
#> 6 A010 P1 15
#> 7 A010 P2 1
#> 8 A010 P1 1
#> 9 A1 P2 5
#> 10 A1 P1 15
#> 11 A1 P1 5
#> 12 A1 P2 1
#> 13 A1 P1 1
#> 14 A1 P2 15
#> 15 A1 P2 10
#> 16 A1 P1 10
#> 17 A10 P2 1
#> 18 A10 P2 5
#> 19 A10 P2 15
#> 20 A10 P1 5
#> 21 A10 P1 1
#> 22 A10 P1 10
#> 23 A10 P2 10
#> 24 A10 P1 15
#> 25 A2 P1 5
#> 26 A2 P2 5
#> 27 A2 P1 1
#> 28 A2 P1 15
#> 29 A2 P2 15
#> 30 A2 P1 10
#> 31 A2 P2 1
#> 32 A2 P2 10
#> 33 A25 P2 5
#> 34 A25 P1 15
#> 35 A25 P1 5
#> 36 A25 P2 1
#> 37 A25 P1 10
#> 38 A25 P2 10
#> 39 A25 P2 15
#> 40 A25 P1 1
# arrange_alphanum function sorts alphanumerically
arrange_alphanum(df, v1)
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A1 P2 5
#> 2 A1 P1 15
#> 3 A1 P1 5
#> 4 A1 P2 1
#> 5 A1 P1 1
#> 6 A1 P2 15
#> 7 A1 P2 10
#> 8 A1 P1 10
#> 9 A2 P1 5
#> 10 A2 P2 5
#> 11 A2 P1 1
#> 12 A2 P1 15
#> 13 A2 P2 15
#> 14 A2 P1 10
#> 15 A2 P2 1
#> 16 A2 P2 10
#> 17 A010 P1 10
#> 18 A010 P2 10
#> 19 A010 P2 15
#> 20 A010 P2 5
#> 21 A010 P1 5
#> 22 A010 P1 15
#> 23 A010 P2 1
#> 24 A010 P1 1
#> 25 A10 P2 1
#> 26 A10 P2 5
#> 27 A10 P2 15
#> 28 A10 P1 5
#> 29 A10 P1 1
#> 30 A10 P1 10
#> 31 A10 P2 10
#> 32 A10 P1 15
#> 33 A25 P2 5
#> 34 A25 P1 15
#> 35 A25 P1 5
#> 36 A25 P2 1
#> 37 A25 P1 10
#> 38 A25 P2 10
#> 39 A25 P2 15
#> 40 A25 P1 1
# arrange_alphanum(df, v1, desc = FALSE) # the same
# arrange_alphanum(df, v1, desc = NA) # the same
# sort first by v2 (ascending), then by v1 (ascending)
arrange_alphanum(df, v2, v1)
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A1 P1 15
#> 2 A1 P1 5
#> 3 A1 P1 1
#> 4 A1 P1 10
#> 5 A2 P1 5
#> 6 A2 P1 1
#> 7 A2 P1 15
#> 8 A2 P1 10
#> 9 A010 P1 10
#> 10 A010 P1 5
#> 11 A010 P1 15
#> 12 A010 P1 1
#> 13 A10 P1 5
#> 14 A10 P1 1
#> 15 A10 P1 10
#> 16 A10 P1 15
#> 17 A25 P1 15
#> 18 A25 P1 5
#> 19 A25 P1 10
#> 20 A25 P1 1
#> 21 A1 P2 5
#> 22 A1 P2 1
#> 23 A1 P2 15
#> 24 A1 P2 10
#> 25 A2 P2 5
#> 26 A2 P2 15
#> 27 A2 P2 1
#> 28 A2 P2 10
#> 29 A010 P2 10
#> 30 A010 P2 15
#> 31 A010 P2 5
#> 32 A010 P2 1
#> 33 A10 P2 1
#> 34 A10 P2 5
#> 35 A10 P2 15
#> 36 A10 P2 10
#> 37 A25 P2 5
#> 38 A25 P2 1
#> 39 A25 P2 10
#> 40 A25 P2 15
# arrange_alphanum(df, v2, v1, desc = FALSE) # the same
# arrange_alphanum(df, v2, v1, desc = c(FALSE, FALSE)) # the same
# sort by v2 (ascending), then v1 (descending)
arrange_alphanum(df, v2, v1, desc = c(FALSE, TRUE))
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A25 P1 15
#> 2 A25 P1 5
#> 3 A25 P1 10
#> 4 A25 P1 1
#> 5 A10 P1 5
#> 6 A10 P1 1
#> 7 A10 P1 10
#> 8 A10 P1 15
#> 9 A010 P1 10
#> 10 A010 P1 5
#> 11 A010 P1 15
#> 12 A010 P1 1
#> 13 A2 P1 5
#> 14 A2 P1 1
#> 15 A2 P1 15
#> 16 A2 P1 10
#> 17 A1 P1 15
#> 18 A1 P1 5
#> 19 A1 P1 1
#> 20 A1 P1 10
#> 21 A25 P2 5
#> 22 A25 P2 1
#> 23 A25 P2 10
#> 24 A25 P2 15
#> 25 A10 P2 1
#> 26 A10 P2 5
#> 27 A10 P2 15
#> 28 A10 P2 10
#> 29 A010 P2 10
#> 30 A010 P2 15
#> 31 A010 P2 5
#> 32 A010 P2 1
#> 33 A2 P2 5
#> 34 A2 P2 15
#> 35 A2 P2 1
#> 36 A2 P2 10
#> 37 A1 P2 5
#> 38 A1 P2 1
#> 39 A1 P2 15
#> 40 A1 P2 10
# sort by v2 (descending), then v1 (ascending)
arrange_alphanum(df, v2, v1, desc = c(TRUE, FALSE))
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A1 P2 5
#> 2 A1 P2 1
#> 3 A1 P2 15
#> 4 A1 P2 10
#> 5 A2 P2 5
#> 6 A2 P2 15
#> 7 A2 P2 1
#> 8 A2 P2 10
#> 9 A010 P2 10
#> 10 A010 P2 15
#> 11 A010 P2 5
#> 12 A010 P2 1
#> 13 A10 P2 1
#> 14 A10 P2 5
#> 15 A10 P2 15
#> 16 A10 P2 10
#> 17 A25 P2 5
#> 18 A25 P2 1
#> 19 A25 P2 10
#> 20 A25 P2 15
#> 21 A1 P1 15
#> 22 A1 P1 5
#> 23 A1 P1 1
#> 24 A1 P1 10
#> 25 A2 P1 5
#> 26 A2 P1 1
#> 27 A2 P1 15
#> 28 A2 P1 10
#> 29 A010 P1 10
#> 30 A010 P1 5
#> 31 A010 P1 15
#> 32 A010 P1 1
#> 33 A10 P1 5
#> 34 A10 P1 1
#> 35 A10 P1 10
#> 36 A10 P1 15
#> 37 A25 P1 15
#> 38 A25 P1 5
#> 39 A25 P1 10
#> 40 A25 P1 1
# sort by v2 (descending), v1 (descending)
arrange_alphanum(df, v2, v1, desc = TRUE)
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A25 P2 5
#> 2 A25 P2 1
#> 3 A25 P2 10
#> 4 A25 P2 15
#> 5 A10 P2 1
#> 6 A10 P2 5
#> 7 A10 P2 15
#> 8 A10 P2 10
#> 9 A010 P2 10
#> 10 A010 P2 15
#> 11 A010 P2 5
#> 12 A010 P2 1
#> 13 A2 P2 5
#> 14 A2 P2 15
#> 15 A2 P2 1
#> 16 A2 P2 10
#> 17 A1 P2 5
#> 18 A1 P2 1
#> 19 A1 P2 15
#> 20 A1 P2 10
#> 21 A25 P1 15
#> 22 A25 P1 5
#> 23 A25 P1 10
#> 24 A25 P1 1
#> 25 A10 P1 5
#> 26 A10 P1 1
#> 27 A10 P1 10
#> 28 A10 P1 15
#> 29 A010 P1 10
#> 30 A010 P1 5
#> 31 A010 P1 15
#> 32 A010 P1 1
#> 33 A2 P1 5
#> 34 A2 P1 1
#> 35 A2 P1 15
#> 36 A2 P1 10
#> 37 A1 P1 15
#> 38 A1 P1 5
#> 39 A1 P1 1
#> 40 A1 P1 10
# arrange_alphanum(df, v2, v1, desc = c(TRUE, TRUE)) # the same
# sort by v2 (descending), v1 (ascending), v3 (descending)
arrange_alphanum(df, v2, v1, v3, desc = c(TRUE, FALSE, TRUE))
#> # A tibble: 40 × 3
#> v1 v2 v3
#> <chr> <chr> <dbl>
#> 1 A1 P2 15
#> 2 A1 P2 10
#> 3 A1 P2 5
#> 4 A1 P2 1
#> 5 A2 P2 15
#> 6 A2 P2 10
#> 7 A2 P2 5
#> 8 A2 P2 1
#> 9 A010 P2 15
#> 10 A010 P2 10
#> 11 A010 P2 5
#> 12 A010 P2 1
#> 13 A10 P2 15
#> 14 A10 P2 10
#> 15 A10 P2 5
#> 16 A10 P2 1
#> 17 A25 P2 15
#> 18 A25 P2 10
#> 19 A25 P2 5
#> 20 A25 P2 1
#> 21 A1 P1 15
#> 22 A1 P1 10
#> 23 A1 P1 5
#> 24 A1 P1 1
#> 25 A2 P1 15
#> 26 A2 P1 10
#> 27 A2 P1 5
#> 28 A2 P1 1
#> 29 A010 P1 15
#> 30 A010 P1 10
#> 31 A010 P1 5
#> 32 A010 P1 1
#> 33 A10 P1 15
#> 34 A10 P1 10
#> 35 A10 P1 5
#> 36 A10 P1 1
#> 37 A25 P1 15
#> 38 A25 P1 10
#> 39 A25 P1 5
#> 40 A25 P1 1
# -----------------------------------------------
# Example with NA and blank strings
(df_special <- tibble::tibble(v1 = c("A", "", "B", NA, "C")))
#> # A tibble: 5 × 1
#> v1
#> <chr>
#> 1 "A"
#> 2 ""
#> 3 "B"
#> 4 NA
#> 5 "C"
# sort with NA first, blanks first (default)
arrange_alphanum(df_special, v1, na_last = FALSE, blank_last = FALSE)
#> # A tibble: 5 × 1
#> v1
#> <chr>
#> 1 ""
#> 2 "A"
#> 3 "B"
#> 4 "C"
#> 5 NA
# sort with NA last, blanks last
arrange_alphanum(df_special, v1, na_last = TRUE, blank_last = TRUE)
#> # A tibble: 5 × 1
#> v1
#> <chr>
#> 1 "A"
#> 2 "B"
#> 3 "C"
#> 4 ""
#> 5 NA