Clean variable (replace NA values, set min_val and max_val)
Usage
clean_var(
data,
var,
na = NA,
min_val = NA,
max_val = NA,
max_cat = NA,
rescale01 = FALSE,
simplify_text = FALSE,
name = NA
)Arguments
- data
A dataset
- var
Name of variable
- na
Value that replaces NA
- min_val
All values < min_val are converted to min_val (var numeric or character)
- max_val
All values > max_val are converted to max_val (var numeric or character)
- max_cat
Maximum number of different factor levels for categorical variable (if more, .OTHER is added)
- rescale01
IF TRUE, value is rescaled between 0 and 1 (var must be numeric)
- simplify_text
If TRUE, a character variable is simplified (trim, upper, ...)
- name
New name of variable (as string)
Examples
library(magrittr)
iris %>% clean_var(Sepal.Width, max_val = 3.5, name = "sepal_width") %>% head()
#> Sepal.Length sepal_width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5.0 3.5 1.4 0.2 setosa
#> 6 5.4 3.5 1.7 0.4 setosa
iris %>% clean_var(Sepal.Width, rescale01 = TRUE) %>% head()
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 0.6250000 1.4 0.2 setosa
#> 2 4.9 0.4166667 1.4 0.2 setosa
#> 3 4.7 0.5000000 1.3 0.2 setosa
#> 4 4.6 0.4583333 1.5 0.2 setosa
#> 5 5.0 0.6666667 1.4 0.2 setosa
#> 6 5.4 0.7916667 1.7 0.4 setosa