Data Visualization using GGPlot2

Data preparation

Create some data (wdata) containing the weights by sex (M for male; F for female):

set.seed(1234)
wdata = data.frame(
        sex = factor(rep(c("F", "M"), each=200)),
        weight = c(rnorm(200, 55), rnorm(200, 58))
        )

# head(wdata, 4)

Loading required R package

Load the ggplot2 package and set the default theme to theme_minimal() with the legend at the top of the plot:

library(ggplot2)
theme_set(
  theme_minimal() +
    theme(legend.position = "top")
  )

Create ECDF plots

# Another option for geom = "point"
ggplot(wdata, aes(x = weight)) +
  stat_ecdf(aes(color = sex,linetype = sex), 
              geom = "step", size = 1.5) +
  scale_color_manual(values = c("#00AFBB", "#E7B800"))+
  labs(y = "f(weight)")

In the above plots, you can see that:

• about 25% of our females are shorter than 50 inches
• about 50% of males are shorter than 58 inches

Conclusion

This article shows how to create an ECDF plot using the ggplot2 R package.