Appendix A — Data description

A.1 Palmer Penguins

Information about this data are available from palmerpenguins

data(penguins, package = "palmerpenguins")

skimr::skim(penguins)

Data summary

Name	penguins
Number of rows	344
Number of columns	8
_______________________
Column type frequency:
factor	3
numeric	5
________________________
Group variables	None

Variable type: factor

skim_variable	n_missing	complete_rate	ordered	n_unique	top_counts
species	0	1.00	FALSE	3	Ade: 152, Gen: 124, Chi: 68
island	0	1.00	FALSE	3	Bis: 168, Dre: 124, Tor: 52
sex	11	0.97	FALSE	2	mal: 168, fem: 165

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
bill_length_mm	2	0.99	43.92	5.46	32.1	39.23	44.45	48.5	59.6	▃▇▇▆▁
bill_depth_mm	2	0.99	17.15	1.97	13.1	15.60	17.30	18.7	21.5	▅▅▇▇▂
flipper_length_mm	2	0.99	200.92	14.06	172.0	190.00	197.00	213.0	231.0	▂▇▃▅▂
body_mass_g	2	0.99	4201.75	801.95	2700.0	3550.00	4050.00	4750.0	6300.0	▃▇▆▃▂
year	0	1.00	2008.03	0.82	2007.0	2007.00	2008.00	2009.0	2009.0	▇▁▇▁▇

A.2 Cancer Registry

cancer_reg <- readr::read_csv(here::here("data/cancer_reg.csv")) 

Rows: 527 Columns: 20
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (3): County, state, group
dbl (17): mortality_rate, number_death, cancer_incidence, number_cases, popu...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

skimr::skim(cancer_reg)

Data summary

Name	cancer_reg
Number of rows	527
Number of columns	20
_______________________
Column type frequency:
character	3
numeric	17
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
County	0	1	16	38	0	527	0
state	0	1	4	14	0	48	0
group	0	1	7	7	0	3	0

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
mortality_rate	0	1	181.19	26.75	66.30	163.35	181.80	197.75	292.50	▁▂▇▂▁
number_death	0	1	119.08	155.31	3.00	28.00	58.00	141.50	914.00	▇▁▁▁▁
cancer_incidence	0	1	450.87	50.24	211.10	421.55	453.55	487.15	630.40	▁▁▇▆▁
number_cases	0	1	409.08	568.85	6.00	76.00	158.00	453.50	2841.00	▇▁▁▁▁
population_2015	0	1	59408.13	90106.98	1130.00	11343.50	25594.00	64463.00	734871.00	▇▁▁▁▁
age	0	1	41.00	5.02	22.30	38.10	40.90	43.80	56.60	▁▂▇▅▁
income	0	1	45918.68	11779.18	23047.00	38017.50	44065.00	51414.50	108477.00	▅▇▂▁▁
poverty	0	1	17.53	6.61	4.20	12.60	16.70	21.30	45.10	▅▇▃▁▁
household	0	1	2.47	0.46	0.02	2.37	2.50	2.63	3.97	▁▁▃▇▁
married	0	1	51.56	6.91	23.10	48.10	52.30	56.30	69.20	▁▁▅▇▁
unemployed	0	1	8.09	3.25	0.70	5.90	8.00	9.70	22.60	▂▇▃▁▁
medicare	0	1	19.63	5.91	2.60	15.50	19.40	23.45	41.40	▁▇▇▂▁
white	0	1	83.10	17.16	11.01	75.81	90.24	95.41	100.00	▁▁▁▂▇
black	0	1	10.36	16.07	0.00	0.68	2.28	12.45	84.87	▇▁▁▁▁
asian	0	1	0.99	1.67	0.00	0.24	0.52	1.13	21.28	▇▁▁▁▁
BirthRate	0	1	5.58	1.98	0.00	4.54	5.38	6.42	17.88	▁▇▁▁▁
random_n	0	1	0.19	0.10	0.00	0.10	0.19	0.28	0.35	▆▇▆▇▇