Display a Pairwise Matrix Table in the Console

Usage

pairwise_matrix(
  display,
  title = NULL,
  name = "Pairwise Matrix",
  diag_1 = TRUE,
  digits = 3,
  layout_view = FALSE,
  layout_center = FALSE,
  center_table = FALSE,
  border_char = getOption("tab_default")$border_char,
  style = list(),
  ...
)

corr_matrix(
  display,
  title = NULL,
  diag_1 = TRUE,
  digits = 3,
  layout_view = FALSE,
  layout_center = FALSE,
  center_table = FALSE,
  border_char = getOption("tab_default")$border_char,
  style = list(),
  ...
)

Arguments

display: A pairwise_spec object from new_pairwise_data(), or a plain symmetric matrix (e.g. from cor()).
title: Label shown above the table. Auto-detected from a title attribute on the spec if present; falls back to name.
name: Short name used in the layout legend box header. Default "Pairwise Matrix".
diag_1: If TRUE, diagonal cells always show "1". Default TRUE.
digits: Decimal places for numeric formatting. Default 3.
layout_view: Show a layout legend box above the table? Default FALSE.
layout_center: Center the layout box in the terminal? Default FALSE.
center_table: Center table in terminal? Default FALSE.
border_char: Border character. Default from getOption("tab_default").
style: A style list. Keys match the extra field names passed to new_pairwise_data() (e.g. rho, pval, bf), plus title and border_text.
...: Reserved for future use.

Value

Invisibly returns the rendered character matrix.

Examples

# From a plain correlation matrix
pairwise_matrix(cor(mtcars[, 1:4]), title = "Pearson Correlation Matrix")
#> 
#>            Pearson Correlation Matrix           
#> ────────────────────────────────────────────────
#>   Variable    mpg      cyl      disp      hp    
#> ────────────────────────────────────────────────
#>   mpg          1      -0.852   -0.848   -0.776  
#> ────────────────────────────────────────────────
#>   cyl        -0.852     1       0.902    0.832  
#> ────────────────────────────────────────────────
#>   disp       -0.848    0.902     1       0.791  
#> ────────────────────────────────────────────────
#>   hp         -0.776    0.832    0.791     1     
#> ────────────────────────────────────────────────

# Customizable example
spec = new_pairwise_data(
    var1 = c("a", "a", "b"),
    var2 = c("b", "c", "c"),
    rho = c("0.89", "0.79", "0.66"),
    pval = c("<0.001", "<0.001", "<0.001")
)
pairwise_matrix(spec, title = "Pearson Correlation Matrix", layout_view = TRUE)
#> 
#> ┌───────────────────────────┐
#> | Layout for Pairwise Matri |
#> ├───────────────────────────┤
#> |          < rho >          |
#> |         < pval >          |
#> └───────────────────────────┘
#> 
#> 
#>     Pearson Correlation Matrix    
#> ──────────────────────────────────
#>   Variable     a        b      c  
#> ──────────────────────────────────
#>   a                               
#>                                   
#> ──────────────────────────────────
#>   b           0.89                
#>              <0.001               
#> ──────────────────────────────────
#>   c           0.79     0.66       
#>              <0.001   <0.001      
#> ──────────────────────────────────