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 -0.218  -2.78 0.000443 0.5   -0.317 
#>  2 1              2 -0.330  -2.66 0.00117  0.508 -0.394 
#>  3 1              3  0.392  -2.53 0.00275  0.516  0.0840
#>  4 1              4 -0.299  -2.41 0.00584  0.524 -0.372 
#>  5 1              5 -0.0765 -2.28 0.0112   0.533 -0.221 
#>  6 1              6 -1.19   -2.16 0.0193   0.541 -1.15  
#>  7 1              7  0.896  -2.03 0.0304   0.549  0.422 
#>  8 1              8 -0.967  -1.91 0.0440   0.557 -0.907 
#>  9 1              9  0.391  -1.79 0.0596   0.565  0.0835
#> 10 1             10  0.477  -1.66 0.0767   0.573  0.139 
#> # … with 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")