README.md

In malcolmbarrett/ggecdf: Calculate Weighted and Unweighted 'ECDFs' for 'ggplot2'

ggecdf

The goal of ggecdf is to easily create weighted and unweighted empirical cumulative distributions (ECDFs) in ggplot2

Installation

You can install the development version of ggecdf from GitHub with:

# install.packages("devtools")
devtools::install_github("malcolmbarrett/ggecdf")

Example

geom_ecdf() allows you to create ECDFs based on ggplot’s stat_ecdf()

library(ggecdf)
library(ggplot2)
# dataset with weights
nhefs_weights <- tidysmd::nhefs_weights

ggplot(
  nhefs_weights,
  aes(x = smokeyrs, color = factor(qsmk))
) +
  geom_ecdf() +
  xlab("Smoking Years") +
  ylab("Proportion <= x (unweighted)")

Additionally, geom_ecdf() supports a weights aesthetic to calculate weighted ECDFs. For instance, here’s the same variables weighted by an ATO weight:

ggplot(
  nhefs_weights,
  aes(x = smokeyrs, color = factor(qsmk))
) +
  geom_ecdf(aes(weights = w_ato)) +
  xlab("Smoking Years") +
  ylab("Proportion <= x (weighted)")

malcolmbarrett/ggecdf documentation built on Dec. 21, 2021, 1:45 p.m.