Rank the data of numeric variables

Rank the values of numeric variables, for example, in descending order, and then returns the result along with tidyverse code used to generate it. See row_number and percent_rank.

Usage

rank_vars(data, vars, rank_type = c("min", "dense", "percent"))

Arguments

data

a dataframe with the variables to rank

vars

a character vector of numeric variables in data to rank

rank_type

either "min", "dense" or "percent", see row_number, percent_rank

Value

the original dataframe containing new columns with the ranks of the variables in vars with tidyverse code attached

See also

code

Author

Zhaoming Su

Examples

ranked <- rank_vars(iris, vars = c("Sepal.Length", "Petal.Length"))
cat(code(ranked))
#> iris |> dplyr::mutate(Sepal.Length.min_rank = dplyr::min_rank(Sepal.Length), .after = Sepal.Length) |> dplyr::mutate(Petal.Length.min_rank = dplyr::min_rank(   Petal.Length), .after = Petal.Length)
head(ranked)
#>   Sepal.Length Sepal.Length.min_rank Sepal.Width Petal.Length
#> 1          5.1                    33         3.5          1.4
#> 2          4.9                    17         3.0          1.4
#> 3          4.7                    10         3.2          1.3
#> 4          4.6                     6         3.1          1.5
#> 5          5.0                    23         3.6          1.4
#> 6          5.4                    47         3.9          1.7
#>   Petal.Length.min_rank Petal.Width Species
#> 1                    12         0.2  setosa
#> 2                    12         0.2  setosa
#> 3                     5         0.2  setosa
#> 4                    25         0.2  setosa
#> 5                    12         0.2  setosa
#> 6                    45         0.4  setosa