visualisation_recipe.easycor_test {correlation} | R Documentation |
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.
## 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, ...)
x |
A correlation object. |
show_data |
Show data. For correlation matrices, can be |
show_text |
Show labels with matrix values. |
... |
Other arguments passed to other functions. |
show_legend |
Show legend. Can be set to |
tile, point, text, scale, scale_fill, smooth, labs |
Additional aesthetics and parameters for the geoms (see customization example). |
type |
Alias for |
# ============================================== # Correlation Test # ============================================== if (require("see")) { 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 ) } # ============================================== # Correlation Matrix # ============================================== if (require("see")) { 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() } # ============================================== # Correlation Results (easycorrelation) # ============================================== if (require("see") && require("tidygraph") && require("ggraph")) { rez <- correlation(iris) layers <- visualisation_recipe(rez) layers plot(layers) }