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The plot() method for the parameters::principal_components() function.

Usage

# S3 method for see_parameters_pca
plot(
  x,
  type = c("bar", "line"),
  size_text = 3.5,
  text_color = "black",
  size = 1,
  show_labels = TRUE,
  ...
)

Arguments

x

An object.

type

Character vector, indicating the type of plot.

size_text

Numeric value specifying size of text labels.

text_color

Character specifying color of text labels.

size

Depending on type, a numeric value specifying size of bars, lines, or segments.

show_labels

Logical. If TRUE, text labels are displayed.

...

Arguments passed to or from other methods.

Value

A ggplot2-object.

Examples

library(parameters)
data(mtcars)
result <- principal_components(mtcars[, 1:7], n = "all", threshold = 0.2)
result
#> # Loadings from Principal Component Analysis (no rotation)
#> 
#> Variable |  PC1  |  PC2  | PC3  |  PC4  | PC5  |  PC6  | Complexity
#> -------------------------------------------------------------------
#> mpg      | -0.93 |       |      | -0.30 |      |       |    1.30   
#> cyl      | 0.96  |       |      |       |      | -0.21 |    1.18   
#> disp     | 0.95  |       |      | -0.23 |      |       |    1.16   
#> hp       | 0.87  | 0.36  |      |       | 0.30 |       |    1.64   
#> drat     | -0.75 | 0.48  | 0.44 |       |      |       |    2.47   
#> wt       | 0.88  | -0.35 | 0.26 |       |      |       |    1.54   
#> qsec     | -0.54 | -0.81 |      |       |      |       |    1.96   
#> 
#> The 6 principal components accounted for 99.30% of the total variance of the original data (PC1 = 72.66%, PC2 = 16.52%, PC3 = 4.93%, PC4 = 2.26%, PC5 = 1.85%, PC6 = 1.08%).
#> 
plot(result)
#> Warning: Removed 25 rows containing missing values (position_stack).
#> Warning: Removed 25 rows containing missing values (geom_text).