| Title: | Customisable Ranking of Numerical and Categorical Data |
| Version: | 0.1.1 |
| Description: | Provides a flexible alternative to the built-in rank() function called smartrank(). Optionally rank categorical variables by frequency (instead of in alphabetical order), and control whether ranking is based on descending/ascending order. smartrank() is suitable for both numerical and categorical data. |
| License: | MIT + file LICENSE |
| Suggests: | covr, dplyr, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 2 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| URL: | https://github.com/selkamand/rank, https://selkamand.github.io/rank/ |
| BugReports: | https://github.com/selkamand/rank/issues |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2024-12-01 21:59:58 UTC; selkamand |
| Author: | Sam El-Kamand 
[aut, cre, cph] |
| Maintainer: | Sam El-Kamand <sam.elkamand@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-12-01 22:30:02 UTC |
Rank a vector based on either alphabetical or frequency order
Description
This function acts as a drop-in replacement for the base rank() function with the added option to:
Rank categorical factors based on frequency instead of alphabetically
Rank in descending or ascending order
Usage
smartrank(
x,
sort_by = c("alphabetical", "frequency"),
desc = FALSE,
ties.method = "average",
na.last = TRUE,
verbose = TRUE
)
Arguments
x |
A numeric, character, or factor vector |
sort_by |
Sort ranking either by "alphabetical" or "frequency" . Default is "alphabetical" |
desc |
A logical indicating whether the ranking should be in descending ( TRUE ) or ascending ( FALSE ) order. When input is numeric, ranking is always based on numeric order. |
ties.method |
a character string specifying how ties are treated, see ‘Details’; can be abbreviated. |
na.last |
a logical or character string controlling the treatment
of |
verbose |
verbose (flag) |
Details
If x includes ‘ties’ (equal values), the ties.method argument determines how the rank value is decided. Must be one of:
-
average: replaces integer ranks of tied values with their average (default)
-
first: first-occurring value is assumed to be the lower rank (closer to one)
-
last: last-occurring value is assumed to be the lower rank (closer to one)
-
max or min: integer ranks of tied values are replaced with their maximum and minimum respectively (latter is typical in sports-ranking)
-
random which of the tied values are higher / lower rank is randomly decided.
NA values are never considered to be equal: for na.last = TRUE and na.last = FALSE they are given distinct ranks in the order in which they occur in x.
Value
The ranked vector
Note
When sort_by = "frequency", ties based on frequency are broken by alphabetical order of the terms
When sort_by = "frequency" and input is character, ties.method is ignored. each distinct element level gets its own rank, and each rank is 1 unit away from the next element, irrespective of how many duplicates
Examples
# ------------------
## CATEGORICAL INPUT
# ------------------
fruits <- c("Apple", "Orange", "Apple", "Pear", "Orange")
# rank alphabetically
smartrank(fruits)
#> [1] 1.5 3.5 1.5 5.0 3.5
# rank based on frequency
smartrank(fruits, sort_by = "frequency")
#> [1] 2.5 4.5 2.5 1.0 4.5
# rank based on descending order of frequency
smartrank(fruits, sort_by = "frequency", desc = TRUE)
#> [1] 1.5 3.5 1.5 5.0 3.5
# sort fruits vector based on rank
ranks <- smartrank(fruits,sort_by = "frequency", desc = TRUE)
fruits[order(ranks)]
#> [1] "Apple" "Apple" "Orange" "Orange" "Pear"
# ------------------
## NUMERICAL INPUT
# ------------------
# rank numerically
smartrank(c(1, 3, 2))
#> [1] 1 3 2
# rank numerically based on descending order
smartrank(c(1, 3, 2), desc = TRUE)
#> [1] 3 1 2
# always rank numeric vectors based on values, irrespective of sort_by
smartrank(c(1, 3, 2), sort_by = "frequency")
#> smartrank: Sorting a non-categorical variable. Ignoring `sort_by` and sorting numerically
#> [1] 1 3 2