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Datasaurus Dozen (wide) data

Source: R/Datasaurus-package.r
datasaurus_dozen_wide.Rd

A dataset demonstrating the utility of visualization. These 12 datasets are equal in standard measures: mean, standard deviation, and Pearson's correlation.

Usage

datasaurus_dozen_wide

Format

A data frame with 142 rows and 26 variables:

  • away_x: x-values for the away dataset

  • away_y: y-values for the away dataset

  • bullseye_x: x-values for the bullseye dataset

  • bullseye_y: y-values for the bullseye dataset

  • circle_x: x-values for the circle dataset

  • circle_y: y-values for the circle dataset

  • dino_x: x-values for dinosaur dataset!

  • dino_y: y-values for dinosaur dataset!

  • dots_x: x-values for the dots dataset

  • dots_y: y-values for the dots dataset

  • h_lines_x: x-values for the h_lines dataset

  • h_lines_y: y-values for the h_lines dataset

  • high_lines_x: x-values for the high_lines dataset

  • high_lines_y: y-values for the high_lines dataset

  • slant_down_x: x-values for the slant_down dataset

  • slant_down_y: y-values for the slant_down dataset

  • slant_up_x: x-values for the slant_up dataset

  • slant_up_y: y-values for the slant_up dataset

  • star_x: x-values for the star dataset

  • star_y: y-values for the star dataset

  • v_lines_x: x-values for the v_lines dataset

  • v_lines_y: y-values for the v_lines dataset

  • wide_lines_x: x-values for the wide_lines dataset

  • wide_lines_y: y-values for the wide_lines dataset

  • x_shape_x: x-values for the x_shape dataset

  • x_shape_y: y-values for the x_shape dataset

References

Matejka, J., & Fitzmaurice, G. (2017). Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing. CHI 2017 Conference proceedings: ACM SIGCHI Conference on Human Factors in Computing Systems. Retrieved from https://www.autodeskresearch.com/publications/samestats.

Examples

# Save current settings
state <- par("mar", "mfrow")

# Base R Plots
par(mfrow = c(5, 3), mar=c(1, 3, 3, 1))

nms <- names(datasaurus_dozen_wide)
for (i in seq(1, 25, by = 2)){
  nm <- substr(nms[i], 1, nchar(nms[i]) - 2)
  plot(datasaurus_dozen_wide[[nms[i]]],
       datasaurus_dozen_wide[[nms[i+1]]],
       xlab = "", ylab = "", main = nm)
}

#reset settings
par(state)