README.md

In jtr13/redav: R for EDAV

Joyce Robbins 2024-01-17

redav

This package will eventually contain functions, data, and templates to accompany data visualization courses.

If you encounter problems or have questions, please open an issue or start/contribute to a discussion.

As of now, it contains two functions: draw_biplot() and plot_missing().

There are other options for drawing biplots in the ggplot2 framework; ggbiplot() in the ordr package is an excellent choice. The main contributions of draw_biplot() are ease of use and option to calibrate only one of the axes. Calibration calculations are performed by calibrate() in the calibrate package.

Currently, draw_biplot() takes a data frame, performs principal components analysis (PCA) on the numeric columns using prcomp() and draws a biplot using the first non-numeric column as labels for the principal component scores (points). Additional options besides PCA may be added in the future.

plot_missing() was designed as a replacement for extracat::visna() which is no longer available on CRAN. It has improved labeling and the option to label axes as percents or numbers.

Examples

draw_biplot()

library(redav)
draw_biplot(attitude)

draw_biplot(attitude, key_axis = "raises") + 
  ggplot2::ggtitle("The Chatterjee-Price Attitude Data", 
          sub = "package: datasets (base R)")

s77 <- as.data.frame(state.x77)
s77$state_name <- rownames(s77)
draw_biplot(s77)

draw_biplot(s77, key_axis = "Murder", ticklab = 0:16, project = FALSE,
            point_color="lightblue") + ggplot2::theme_classic()

draw_biplot(s77, mult = 1, point_color = "pink")

draw_biplot(s77, points = FALSE)

plot_missing()

library(redav)
data(CHAIN, package = "mi")
plot_missing(CHAIN)

plot_missing(CHAIN, percent = FALSE)

plot_missing(CHAIN, max_rows = 4)

plot_missing(CHAIN, max_cols = 3)

plot_missing(CHAIN, num_char = 5)

plot_missing(CHAIN, max_rows = 4, max_cols = 3, num_char = 5, percent = FALSE)

plot_missing(mtcars)

Rendered from Readme.Rmd.

jtr13/redav documentation built on March 31, 2024, 11:56 a.m.