The goal of palmerpenguins is to provide a great dataset for data exploration & visualization, as an alternative to iris.
Installation
You can install the development version from
GitHub with:
# install.packages("remotes")
remotes::install_github("allisonhorst/palmerpenguins")
R
About the data
Data were collected and made available by Dr. Kristen
and the Palmer Station, Antarctica LTER, a
member of the Long Term Ecological Research
The palmerpenguins package contains two datasets.
library(palmerpenguins)
data(package = 'palmerpenguins')
R
One is called penguins, and is a simplified version of the raw data;
see ?penguins for more info:
head(penguins)
#> # A tibble: 6 x 8
#> species island bill_length_mm bill_depth_mm flipper_length_… body_mass_g sex
#> <fct> <fct> <dbl> <dbl> <int> <int> <fct>
#> 1 Adelie Torge… 39.1 18.7 181 3750 male
#> 2 Adelie Torge… 39.5 17.4 186 3800 fema…
#> 3 Adelie Torge… 40.3 18 195 3250 fema…
#> 4 Adelie Torge… NA NA NA NA <NA>
#> 5 Adelie Torge… 36.7 19.3 193 3450 fema…
#> 6 Adelie Torge… 39.3 20.6 190 3650 male
#> # … with 1 more variable: year <int>
R
The second dataset is penguins_raw, and contains all the variables and
original names as downloaded; see ?penguins_raw for more info.
head(penguins_raw)
#> # A tibble: 6 x 17
#> studyName `Sample Number` Species Region Island Stage `Individual ID`
#> <chr> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 PAL0708 1 Adelie… Anvers Torge… Adul… N1A1
#> 2 PAL0708 2 Adelie… Anvers Torge… Adul… N1A2
#> 3 PAL0708 3 Adelie… Anvers Torge… Adul… N2A1
#> 4 PAL0708 4 Adelie… Anvers Torge… Adul… N2A2
#> 5 PAL0708 5 Adelie… Anvers Torge… Adul… N3A1
#> 6 PAL0708 6 Adelie… Anvers Torge… Adul… N3A2
#> # … with 10 more variables: `Clutch Completion` <chr>, `Date Egg` <date>,
#> # `Culmen Length (mm)` <dbl>, `Culmen Depth (mm)` <dbl>, `Flipper Length
#> # (mm)` <dbl>, `Body Mass (g)` <dbl>, Sex <chr>, `Delta 15 N (o/oo)` <dbl>,
#> # `Delta 13 C (o/oo)` <dbl>, Comments <chr>
R
Both datasets contain data for 344 penguins. There are 3 different
species of penguins in this dataset, collected from 3 islands in the
Palmer Archipelago, Antarctica.
str(penguins)
#> tibble [344 × 8] (S3: tbl_df/tbl/data.frame)
#> $ species : Factor w/ 3 levels "Adelie","Chinstrap",..: 1 1 1 1 1 1 1 1 1 1 ...
#> $ island : Factor w/ 3 levels "Biscoe","Dream",..: 3 3 3 3 3 3 3 3 3 3 ...
#> $ bill_length_mm : num [1:344] 39.1 39.5 40.3 NA 36.7 39.3 38.9 39.2 34.1 42 ...
#> $ bill_depth_mm : num [1:344] 18.7 17.4 18 NA 19.3 20.6 17.8 19.6 18.1 20.2 ...
#> $ flipper_length_mm: int [1:344] 181 186 195 NA 193 190 181 195 193 190 ...
#> $ body_mass_g : int [1:344] 3750 3800 3250 NA 3450 3650 3625 4675 3475 4250 ...
#> $ sex : Factor w/ 2 levels "female","male": 2 1 1 NA 1 2 1 2 NA NA ...
#> $ year : int [1:344] 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 ...
R
Thank you to Dr. Gorman, Palmer Station LTER and the LTER Network!
Special thanks to Marty Downs (Director, LTER Network Office) for help
regarding the data license & use.
Examples
You can find these and more code examples for exploring palmerpenguins
in vignette("examples").
Penguins are fun to summarize! For example:
library(tidyverse)
penguins %>%
count(species)
#> # A tibble: 3 x 2
#> species n
#> <fct> <int>
#> 1 Adelie 152
#> 2 Chinstrap 68
#> 3 Gentoo 124
penguins %>%
group_by(species) %>%
summarize(across(where(is.numeric), mean, na.rm = TRUE))
#> # A tibble: 3 x 6
#> species bill_length_mm bill_depth_mm flipper_length_mm body_mass_g year
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Adelie 38.8 18.3 190\. 3701\. 2008.
#> 2 Chinstrap 48.8 18.4 196\. 3733\. 2008.
#> 3 Gentoo 47.5 15.0 217\. 5076\. 2008.
R
Penguins are fun to visualize! For example:
#data visualization #visual studio code #visual studio
