Analysis of Ben & Jerry’s Ice Cream Data

ice-cream
code
data-analysis
data-visualization
Author

Byeong-Hak Choe

Published

February 11, 2026

Let’s analyze the starwars data:

ice_cream <- read_csv("https://bcdanl.github.io/data/ben-and-jerry-cleaned.csv")
rmarkdown::paged_table(ice_cream)

Variable Description for ice_cream data.frame

The following describes the variables in the ice_cream data.frame.

…

ice_cream |> 
  skim()
Data summary
Name ice_cream
Number of rows 21974
Number of columns 17
_______________________
Column type frequency:
character 4
logical 8
numeric 5
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
flavor_descr 0 1 3 30 0 50 0
size1_descr 0 1 9 9 0 2 0
region 0 1 4 7 0 4 0
race 0 1 5 5 0 4 0

Variable type: logical

skim_variable n_missing complete_rate mean count
usecoup 0 1 0.11 FAL: 19629, TRU: 2345
married 0 1 0.60 TRU: 13276, FAL: 8698
hispanic_origin 0 1 0.05 FAL: 20919, TRU: 1055
microwave 0 1 0.98 TRU: 21567, FAL: 407
dishwasher 0 1 0.77 TRU: 16983, FAL: 4991
sfh 0 1 0.73 TRU: 16076, FAL: 5898
internet 0 1 0.84 TRU: 18529, FAL: 3445
tvcable 34 1 0.64 TRU: 13954, FAL: 7986

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
priceper1 0 1 3.31 0.67 0 3 3.34 3.59 9.48 ▁▇▂▁▁
household_id 0 1 16612005.04 11685954.46 2000358 8142253 8401573.00 30183891.00 30440689.00 ▂▇▁▁▇
household_income 0 1 125290.80 57188.36 40000 80000 110000.00 170000.00 310000.00 ▇▃▅▂▁
household_size 0 1 2.46 1.34 1 2 2.00 3.00 9.00 ▇▃▁▁▁
couponper1 0 1 0.13 0.52 0 0 0.00 0.00 8.98 ▇▁▁▁▁

Flavor Description

flavor_desc <- ice_cream |> 
  count(flavor_descr) |> 
  arrange(-n)
icecream_sub <- ice_cream |> 
  filter(flavor_descr %in% flavor_desc$flavor_descr[1:5])

ggplot(icecream_sub,
       aes(x = priceper1,
           fill = flavor_descr)) +
  geom_density(alpha = .25)