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Classify a Variable as Continuous or Categorical

Source: R/eda-plots.R
eda_classify_var.Rd

Replicates the type-detection logic from Barplot_Scatterplot_Function.R: a numeric column is treated as categorical when all non-missing values are non-negative whole numbers with no more than unique_limit distinct values.

Usage

eda_classify_var(
  x,
  unique_limit = 6L,
  unique_bound = 100,
  var_name = NULL,
  type_overrides = NULL
)

Arguments

x

A vector (one column of a data frame).

unique_limit

Integer threshold. Numeric columns with more distinct values than this are classified as "Cont". Default 6.

unique_bound

Integer threshold. Numeric columns that contain any values greater than this are classified as "Cont", regardless of number of distinct values. Default 100

var_name

A string containing the name of the variable/column. Default NULL

type_overrides

A named vector of variables and variable types ("Cont", "Cat_Num", or "Cat_Char") to manually set their classifications, e.g., c(severity = "Cat_Num"). Default NULL

Value

A length-1 character: "Cont", "Cat_Num", or "Cat_Char".

See also

hv_eda(), eda_select_vars()

Examples

eda_classify_var(c(0, 1, 1, 0, NA))        # "Cat_Num"
#> [1] "Cat_Num"
eda_classify_var(c(1, 2, 3, 4))            # "Cat_Num"
#> [1] "Cat_Num"
eda_classify_var(rnorm(50))                # "Cont"
#> [1] "Cont"
eda_classify_var(c("A", "B", "A"))         # "Cat_Char"
#> [1] "Cat_Char"