# Pareto Plots for Nominal Distributions

    library(nomiShape)

## Pareto Plot Example

The below example demonstrates how to use the `pareto_plot()` function from the `nomiShape` package to create a Pareto chart for a nominal variable “species” in the `starwars` dataset. Pareto charts help visualize the frequency distribution of categories along with their cumulative percentages.

    pareto(starwars, "species")
    #>          Category Freq cumulative cumulative_percentage
    #> 1           Human   35         35              42.16867
    #> 2           Droid    6         41              49.39759
    #> 3          Gungan    3         44              53.01205
    #> 4        Kaminoan    2         46              55.42169
    #> 5        Mirialan    2         48              57.83133
    #> 6         Twi'lek    2         50              60.24096
    #> 7         Wookiee    2         52              62.65060
    #> 8          Zabrak    2         54              65.06024
    #> 9          Aleena    1         55              66.26506
    #> 10       Besalisk    1         56              67.46988
    #> 11         Cerean    1         57              68.67470
    #> 12       Chagrian    1         58              69.87952
    #> 13       Clawdite    1         59              71.08434
    #> 14            Dug    1         60              72.28916
    #> 15           Ewok    1         61              73.49398
    #> 16      Geonosian    1         62              74.69880
    #> 17           Hutt    1         63              75.90361
    #> 18       Iktotchi    1         64              77.10843
    #> 19        Kaleesh    1         65              78.31325
    #> 20        Kel Dor    1         66              79.51807
    #> 21   Mon Calamari    1         67              80.72289
    #> 22           Muun    1         68              81.92771
    #> 23       Nautolan    1         69              83.13253
    #> 24      Neimodian    1         70              84.33735
    #> 25         Pau'an    1         71              85.54217
    #> 26       Quermian    1         72              86.74699
    #> 27         Rodian    1         73              87.95181
    #> 28        Skakoan    1         74              89.15663
    #> 29      Sullustan    1         75              90.36145
    #> 30     Tholothian    1         76              91.56627
    #> 31        Togruta    1         77              92.77108
    #> 32          Toong    1         78              93.97590
    #> 33      Toydarian    1         79              95.18072
    #> 34     Trandoshan    1         80              96.38554
    #> 35     Vulptereen    1         81              97.59036
    #> 36          Xexto    1         82              98.79518
    #> 37 Yoda's species    1         83             100.00000

Another example using the `mpg` dataset to visualize the distribution of the “manufacturer” variable.

    pareto(mpg, "manufacturer", show_table = FALSE)