char_cor_vars: Cramer's V matrix between categorical variables.

In creditmodel: Toolkit for Credit Modeling, Analysis and Visualization

Description

char_cor_vars is function for calculating Cramer's V matrix between categorical variables. char_cor is function for calculating the correlation coefficient between variables by cremers 'V

Usage

char_cor_vars(dat, x)

char_cor(dat, x_list = NULL, ex_cols = "date$", parallel = FALSE, note = FALSE)

Arguments

dat	A data frame.
x	The name of variable to process.
x_list	Names of independent variables.
ex_cols	A list of excluded variables. Regular expressions can also be used to match variable names. Default is NULL.
parallel	Logical, parallel computing. Default is FALSE.
note	Logical. Outputs info. Default is TRUE.

Value

A list contains correlation index of x with other variables in dat.

Examples

## Not run: 
char_x_list = get_names(dat = UCICreditCard,
types = c('factor', 'character'),
ex_cols = "ID$|date$|default.payment.next.month$", get_ex = FALSE)
 char_cor(dat = UCICreditCard[char_x_list])

## End(Not run)

Example output

Package 'creditmodel' version 1.2.7
                 SEX  EDUCATION   MARRIAGE
SEX       1.00000000 0.03204264 0.03317131
EDUCATION 0.03204264 1.00000000 0.11487308
MARRIAGE  0.03317131 0.11487308 1.00000000

creditmodel documentation built on Jan. 7, 2022, 5:06 p.m.