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)