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# Getting Started with TidyDensity

Source: `vignettes/getting-started.Rmd`
`getting-started.Rmd`

    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 -0.465  -2.75 0.000449 0.321 -0.465
    #>  2 1              2  0.0208 -2.63 0.00124  0.508  0.0208
    #>  3 1              3 -0.463  -2.51 0.00303  0.322 -0.463
    #>  4 1              4 -0.581  -2.38 0.00657  0.281 -0.581
    #>  5 1              5 -0.347  -2.26 0.0127   0.364 -0.347
    #>  6 1              6  2.19   -2.14 0.0219   0.986  2.19
    #>  7 1              7 -0.255  -2.02 0.0342   0.399 -0.255
    #>  8 1              8 -0.0367 -1.90 0.0489   0.485 -0.0367
    #>  9 1              9 -0.567  -1.77 0.0652   0.285 -0.567
    #> 10 1             10 -0.882  -1.65 0.0834   0.189 -0.882
    #> # 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")