visualisation_recipe.easycor_test {correlation}

Visualisation Recipe for 'correlation' Objects

Description

Objects from the correlation package can be easily visualized. You can simply run plot() on them, which will internally call the visualisation_recipe() method to produce a basic ggplot. You can customize this plot ad-hoc or via the arguments described below. See examples here.

Usage

## S3 method for class 'easycor_test'
visualisation_recipe(
  x,
  show_data = "point",
  show_text = "subtitle",
  smooth = NULL,
  point = NULL,
  text = NULL,
  labs = NULL,
  ...
)

## S3 method for class 'easycormatrix'
visualisation_recipe(
  x,
  show_data = "tile",
  show_text = "text",
  show_legend = TRUE,
  tile = NULL,
  point = NULL,
  text = NULL,
  scale = NULL,
  scale_fill = NULL,
  labs = NULL,
  type = show_data,
  ...
)

## S3 method for class 'easycorrelation'
visualisation_recipe(x, ...)

Arguments

x

A correlation object.

show_data

Show data. For correlation matrices, can be "tile" (default) or "point".

show_text

Show labels with matrix values.

...

Other arguments passed to other functions.

show_legend

Show legend. Can be set to FALSE to remove the legend.

tile, point, text, scale, scale_fill, smooth, labs

Additional aesthetics and parameters for the geoms (see customization example).

type

Alias for show_data, for backwards compatibility.

Examples

rez <- cor_test(mtcars, "mpg", "wt")

layers <- visualisation_recipe(rez, labs = list(x = "Miles per Gallon (mpg)"))
layers
plot(layers)

plot(rez,
  show_text = "label",
  point = list(color = "#f44336"),
  text = list(fontface = "bold"),
  show_statistic = FALSE, show_ci = FALSE, stars = TRUE
)




rez <- correlation(mtcars)

x <- cor_sort(as.matrix(rez))
layers <- visualisation_recipe(x)
layers
plot(layers)

#' Get more details using `summary()`
x <- summary(rez, redundant = TRUE, digits = 3)
plot(visualisation_recipe(x))

# Customize
x <- summary(rez)
layers <- visualisation_recipe(x,
  show_data = "points",
  scale = list(range = c(10, 20)),
  scale_fill = list(
    high = "#FF5722",
    low = "#673AB7",
    name = "r"
  ),
  text = list(color = "white"),
  labs = list(title = "My Plot")
)
plot(layers) + theme_modern()




rez <- correlation(iris)

layers <- visualisation_recipe(rez)
layers
plot(layers)