Getting Started with TidyDensity

library(TidyDensity)

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 -0.825 -3.19 0.000448 0.5    -0.788 
#>  2 1              2  0.450 -3.04 0.00124  0.508  -0.0411
#>  3 1              3 -0.696 -2.89 0.00308  0.516  -0.698 
#>  4 1              4  0.507 -2.73 0.00689  0.524  -0.0108
#>  5 1              5  0.691 -2.58 0.0139   0.533   0.0858
#>  6 1              6  1.15  -2.43 0.0256   0.541   0.337 
#>  7 1              7  1.19  -2.28 0.0431   0.549   0.357 
#>  8 1              8  1.67  -2.13 0.0667   0.557   0.641 
#>  9 1              9  2.90  -1.98 0.0961   0.565 Inf     
#> 10 1             10 -0.740 -1.82 0.130    0.573  -0.728 
#> # … with 40 more rows
#> # ℹ Use `print(n = ...)` to see 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")