Numeric X & Y graphs

Quantitative X-Y axis and a third variable.

Refer to data format before plotting.

Saving graphs

See Saving graphs for tips on how to save plots for making figures.

plot_xy_NumGroup: three numeric variables

This example uses “mtcars” dataset to plot mileage per gallon (mpg) vs displacement (disp) grouped by number of gears (also a numeric variable) or carburettors (carb; numeric variable). The continuous colour scheme is applied by default (can be changed by any other colour scheme, such as colorbrewer or viridis if required).

plot_xy_NumGroup(mtcars, 
                 xcol = mpg,          #numeric X
                 ycol = disp,         #numeric Y 
                 NumGroup = gear,     #3rd numeric variable
                 symsize = 3)+     
  labs(title = "3 numeric variables",
       subtitle = "(blue_conti palette)") #applied by default

plot_xy_NumGroup(mtcars, 
                 xcol = mpg,          #numeric X
                 ycol = disp,         #numeric Y 
                 NumGroup = gear,     #3rd numeric variable
                 ColPal = "grey_conti", #greyscale
                 symsize = 3)+     
  labs(title = "3 numeric variables",
       subtitle = "(blue_conti palette)") #applied by default

This next example uses the “trees” data set.

plot_xy_NumGroup(trees, 
                 Height, 
                 Volume, 
                 Girth,
                 ColPal = "yellow_conti",
                 symsize = 4,
                 s_alpha = .8)+
  labs(title = "3 numeric variables",
       subtitle = "(yellow_conti palette)")

Divergent colour scheme, with data from the diamonds dataset

plot_xy_NumGroup(dplyr::filter(diamonds, cut == "Premium" & clarity == "SI1"), 
                 depth, 
                 price, 
                 carat, 
                 s_alpha = .5, 
                 ColPal = "PrGn_div")+ #colschem
  labs(title = "`PrGn_div` colour palette")

plot_xy_CatGroup: two numeric & one categorical variable

This example uses “neuralgia” dataset from the emmeans package. Age and Duration of pain are numeric variables, Treatment, Sex and Pain are categorical.

head(neuralgia, n = 5) #see the dataset

#>   Treatment Sex Age Duration Pain
#> 1         P   F  68        1   No
#> 2         B   M  74       16   No
#> 3         P   F  67       30   No
#> 4         P   M  66       26  Yes
#> 5         B   M  70       22   No

I plot this data with Pain as the grouping factor.

plot_xy_CatGroup(neuralgia,
                 Age,
                 Duration,
                 Pain,
                 symsize = 3,
                 ColPal = "muted",     #palette
                 ColRev = T)+         #reverse colours
  labs(title = "2 numeric & 1 categorical variable",
       subtitle = "(reverse 'muted' palette)")

Same data with faceting to include a 4th factor “Treatment”.

plot_xy_CatGroup(neuralgia,
                 Age,
                 Duration,
                 Pain,
                 Treatment,           #facet
                 symsize = 3,
                 ColPal = "vibrant")+ #palette  
  labs(title = "2 numeric & 1 categorical variable",
       subtitle = "(reverse 'vibrant' palette, facet_wrap)")

The next example uses the same “mtcars” dataset where gear is automatically converted to a categorical variable (even though it is a quantitative variable in the data table) when plot_xy_CatGroup is used. Compare this to the graph above with plot_xy_NumGroup.

plot_xy_CatGroup(mtcars, 
                 xcol = mpg,          #numeric X
                 ycol = disp,         #numeric Y 
                 CatGroup = gear,     #3rd variable
                 symsize = 3)+     
  labs(title = "2 numeric & 3rd converted to factor",
       subtitle = "(`all_grafify` palette)") #applied by default