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XY scatter plot wrapper

Source: R/func_gg.R
ggxy.Rd

Create basic XY scatter plot for quick data exploration. Default to show Pearson correlation coefficient with p-value using ggpubr::stat_cor. For more complex plots, it is recommended to use ggplot2::ggplot2 directly.

Usage

ggxy(
  d,
  x,
  y,
  ...,
  lm = TRUE,
  se = TRUE,
  cor = TRUE,
  pv = NULL,
  nsub = TRUE,
  legend = TRUE,
  asp = 1
)

Arguments

d

<dfr> A data frame.

x, y

<var> Variables for x- and y-axis as unquoted names.

...

Arguments to pass to ggplot2::aes for additional mapping.

lm

<lgl> TRUE to add regression line from linear model.

se

<lgl> TRUE to show standard error with the regression line.

cor

<lgl> TRUE to show Pearson correlation coefficient with p-value.

pv

<dbl> Precision for the p-value, e.g., 0.001 to show 3 decimal places.

nsub

<lgl> Show number of observations.

legend

<lgl> TRUE to show legend.

asp

<num> For aspect.ratio in ggplot2::theme.

Value

A ggplot object.

See also

ggpubr::stat_cor

Examples

mtcars |> ggxy(wt,hp)
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,col=factor(gear))
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,col=factor(gear),legend=FALSE)
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,col=factor(gear),pch=factor(am))
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,nsub=FALSE)
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,pv=0.001)
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,lm=FALSE)

mtcars |> ggxy(wt,hp,se=FALSE)
#> `geom_smooth()` using formula = 'y ~ x'

mtcars |> ggxy(wt,hp,cor=FALSE)
#> `geom_smooth()` using formula = 'y ~ x'