Formatted PCA variance explained table

Produces a styled gt table of variance explained by each principal component, with a colour gradient on cumulative variance.

Usage

tl_table_variance(model, n_components = NULL, digits = 4, ...)

Arguments

model

A tidylearn PCA model object

n_components

Maximum number of components to show (default: all)

digits

Number of decimal places (default: 4)

...

Additional arguments (currently unused)

Value

A gt table object.

Examples

# \donttest{
model <- tl_model(iris[, 1:4], method = "pca")
tl_table_variance(model)


  
PCA Variance Explained
    
Component
      
Std. Dev.
      
Variance
      
Proportion
      
Cumulative
    
PC1
1.7084
2.9185
73.0%
73.0%
PC2
0.9560
0.9140
22.9%
95.8%
PC3
0.3831
0.1468
3.7%
99.5%
PC4
0.1439
0.0207
0.5%
100.0%
tidylearn | pca | n = 150
    
# }