README.md

In EvaMaeRey/ggxmean: Statistical Geoms

ggxmean

The goal of ggxmean is plot the mean of x - and some other things like y!

Installation

The development version from GitHub with:

# install.packages("devtools")
devtools::install_github("EvaMaeRey/ggxmean")

• In-progress long form rationale and package exploration

• Talk MAA Metro NY

Examples

Open flipbook in a new tab

# knitr::opts_chunk$set(eval = F)
options(gganimate.nframes = 60)
library(tidyverse)
library(ggxmean)
#library(transformr) might help w/ animate

## basic example code
cars %>% 
  ggplot() +
  aes(x = speed,
      y = dist) +
  geom_point() + 
  ggxmean::geom_x_mean() +
  ggxmean::geom_x_mean_label() +
  ggxmean::geom_y_mean() +
  ggxmean::geom_xy_means(color = "red",
                size = 5) +
  ggxmean::geom_lm_fitted(color = "goldenrod3",
                          size = 3) +
  ggxmean::geom_lm_pred_int() +
  ggxmean::geom_lm() +
  ggxmean::geom_lm_residuals(linetype = "dashed") +
  ggxmean::geom_lm_conf_int() +
  ggxmean::geom_lm_formula()

palmerpenguins::penguins %>% 
  ggplot() +
  aes(x = bill_length_mm) +
  geom_rug(alpha = .3) +
  geom_histogram(alpha = .4) +
  geom_x_mean() +
  aes(fill = species) + # unexpected behavior here
  aes(color = species) +
  facet_wrap(facets = vars(species)) +
  gganimate::transition_layers()

library(ggxmean)
palmerpenguins::penguins %>% 
  drop_na() %>% 
  ggplot() +
  aes(x = bill_length_mm) +
  aes(y = flipper_length_mm) +
  geom_point() +
  ggxmean:::geom_x_mean() +
  ggxmean:::geom_y_mean() +
  ggxmean:::geom_y_line(alpha = .2) +
  ggxmean:::geom_x_line(alpha = .2) +
  ggxmean:::geom_xdiff() +
  ggxmean:::geom_ydiff() +
  ggxmean:::geom_x1sd(linetype = "dashed") +
  ggxmean:::geom_y1sd(linetype = "dashed") +
  ggxmean:::geom_diffsmultiplied() +
  ggxmean:::geom_xydiffsmean(alpha = 1) +
  ggxmean:::geom_rsq1() +
  ggxmean:::geom_corrlabel() +
  gganimate::transition_layers()

EvaMaeRey/ggxmean documentation built on April 10, 2024, 6:32 p.m.