Plot method for principal component analysis — plot.see_parameters

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

Usage

# S3 method for class 'see_parameters_pca'
plot(
  x,
  type = "bar",
  size_text = 3.5,
  color_text = "black",
  colors = c("#cd201f", "#ffffff", "#0077B5"),
  size = 1,
  show_labels = TRUE,
  arrow_end_gap = 0.07,
  factor_node_size = c(25, 35),
  margins = c(0.3, 0.3),
  names_factors = NULL,
  fill_variables = "#738b8d",
  fill_factors = "#2C3E50",
  ...
)

Arguments

x: An object.
type: Character vector, indicating the type of plot. Options are different shapes to represent component loadings; "bar" (default) for a horizontal bar chart, "line" for a horizontal point and line chart, or "graph" for a graph.
size_text: Numeric value specifying size of text labels.
color_text: Character specifying color of text labels.
colors: Character vector of length three, indicating the colors for low (negative), mid (close to zero), and high (positive) values.
size: Depending on type, a numeric value specifying size of bars, lines, or segments.
show_labels: Logical. If TRUE, text labels are displayed.
arrow_end_gap: Numeric. Specifies the distance between the tip of the edge arrow and the variable node. Adjusting this value prevents the arrow from overlapping or clipping into the variable label. Default is 0.07 (measured in 'snpc' units). This argument is only used if type = "graph".
factor_node_size: Numeric vector of length 2. Determines the minimum and maximum size of the circular factor nodes. Factor nodes are scaled internally based on the proportion of variance they explain. This argument is only used if type = "graph".
margins: Numeric vector of length 2. Adds extra space to the left and right edges of the plot canvas (using ggplot2::expansion). This is particularly useful to prevent long variable labels on the edges from being cut off. This argument is only used if type = "graph".
names_factors: Named character vector. Allows providing custom labels for the factor nodes. The names of the vector must match the original factor names generated by the model (e.g., c("Component 1" = "Extraversion", "Component 2" = "Neuroticism")). This argument is only used if type = "graph".
fill_variables: Character vector. Specifies the fill color for the variable nodes (rectangular labels). Can be a single color hex/name (applied to all variables), a vector of colors matching the exact number of variables, or a named vector to map specific colors to specific variables. This argument is only used if type = "graph".
fill_factors: Character vector. Specifies the fill color for the factor nodes (circular points). Similar to fill_variables, this accepts a single color, a vector of matching length, or a named vector for precise mapping. This argument is only used if type = "graph".
...: 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)