Download palmerpenguins data from Environmental Data Initiative • palmerpenguins

library(palmerpenguins)

Download data from a URL

You can also get this penguin data directly from the Environmental Data Initiative (EDI) using the R code below. Thanks to Julien Brun for the reminder and code below to access & combine them (will get you same data as penguins_raw):

# Adelie penguin data from: https://doi.org/10.6073/pasta/abc50eed9138b75f54eaada0841b9b86

uri_adelie <- "https://portal.edirepository.org/nis/dataviewer?packageid=knb-lter-pal.219.3&entityid=002f3893385f710df69eeebe893144ff"

# Gentoo penguin data from: https://doi.org/10.6073/pasta/2b1cff60f81640f182433d23e68541ce

uri_gentoo <- "https://portal.edirepository.org/nis/dataviewer?packageid=knb-lter-pal.220.3&entityid=e03b43c924f226486f2f0ab6709d2381"

# Chinstrap penguin data from: https://doi.org/10.6073/pasta/409c808f8fc9899d02401bdb04580af7
uri_chinstrap <- "https://portal.edirepository.org/nis/dataviewer?packageid=knb-lter-pal.221.2&entityid=fe853aa8f7a59aa84cdd3197619ef462"

# Combining the URIs
uris <- c(uri_adelie, uri_gentoo, uri_chinstrap)

# Downloading and importing data
library(purrr)
library(readr)
penguins_lter <- map_dfr(uris, read_csv)

Compare to package data

Compared to ?penguins_raw:

head(penguins_raw)
#> # A tibble: 6 × 17
#>   studyName `Sample Number` Species          Region Island Stage `Individual ID`
#>   <chr>               <dbl> <chr>            <chr>  <chr>  <chr> <chr>          
#> 1 PAL0708                 1 Adelie Penguin … Anvers Torge… Adul… N1A1           
#> 2 PAL0708                 2 Adelie Penguin … Anvers Torge… Adul… N1A2           
#> 3 PAL0708                 3 Adelie Penguin … Anvers Torge… Adul… N2A1           
#> 4 PAL0708                 4 Adelie Penguin … Anvers Torge… Adul… N2A2           
#> 5 PAL0708                 5 Adelie Penguin … Anvers Torge… Adul… N3A1           
#> 6 PAL0708                 6 Adelie Penguin … Anvers Torge… Adul… N3A2           
#> # ℹ 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>

But if that looks too messy for you, ?penguins is simpler and tidier:

head(penguins)
#> # A tibble: 6 × 8
#>   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
#>   <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
#> 1 Adelie  Torgersen           39.1          18.7               181        3750
#> 2 Adelie  Torgersen           39.5          17.4               186        3800
#> 3 Adelie  Torgersen           40.3          18                 195        3250
#> 4 Adelie  Torgersen           NA            NA                  NA          NA
#> 5 Adelie  Torgersen           36.7          19.3               193        3450
#> 6 Adelie  Torgersen           39.3          20.6               190        3650
#> # ℹ 2 more variables: sex <fct>, year <int>