# 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`````` 