Skip to contents

Example

This is a basic example which shows you how easy it is to generate data with TidyDensity:

library(TidyDensity)
library(dplyr)
library(ggplot2)

tidy_normal()
#> # A tibble: 50 × 7
#>    sim_number     x      y    dx       dy     p      q
#>    <fct>      <int>  <dbl> <dbl>    <dbl> <dbl>  <dbl>
#>  1 1              1 -0.392 -3.23 0.000243 0.348 -0.392
#>  2 1              2  0.890 -3.08 0.000730 0.813  0.890
#>  3 1              3  0.644 -2.93 0.00190  0.740  0.644
#>  4 1              4  0.524 -2.79 0.00432  0.700  0.524
#>  5 1              5 -0.951 -2.64 0.00864  0.171 -0.951
#>  6 1              6 -0.324 -2.50 0.0155   0.373 -0.324
#>  7 1              7 -0.247 -2.35 0.0254   0.402 -0.247
#>  8 1              8  0.487 -2.20 0.0392   0.687  0.487
#>  9 1              9 -0.442 -2.06 0.0584   0.329 -0.442
#> 10 1             10 -0.171 -1.91 0.0845   0.432 -0.171
#> # ℹ 40 more rows

An example plot of the tidy_normal data.

tn <- tidy_normal(.n = 100, .num_sims = 6)

tidy_autoplot(tn, .plot_type = "density")

tidy_autoplot(tn, .plot_type = "quantile")

tidy_autoplot(tn, .plot_type = "probability")

tidy_autoplot(tn, .plot_type = "qq")

We can also take a look at the plots when the number of simulations is greater than nine. This will automatically turn off the legend as it will become too noisy.

tn <- tidy_normal(.n = 100, .num_sims = 20)

tidy_autoplot(tn, .plot_type = "density")

tidy_autoplot(tn, .plot_type = "quantile")

tidy_autoplot(tn, .plot_type = "probability")

tidy_autoplot(tn, .plot_type = "qq")