
Download palmerpenguins data from Environmental Data Initiative
Source:vignettes/download.Rmd
download.Rmd
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
#> study…¹ Sampl…² Species Region Island Stage Indiv…³ Clutc…⁴ `Date Egg` Culme…⁵
#> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <date> <dbl>
#> 1 PAL0708 1 Adelie… Anvers Torge… Adul… N1A1 Yes 2007-11-11 39.1
#> 2 PAL0708 2 Adelie… Anvers Torge… Adul… N1A2 Yes 2007-11-11 39.5
#> 3 PAL0708 3 Adelie… Anvers Torge… Adul… N2A1 Yes 2007-11-16 40.3
#> 4 PAL0708 4 Adelie… Anvers Torge… Adul… N2A2 Yes 2007-11-16 NA
#> 5 PAL0708 5 Adelie… Anvers Torge… Adul… N3A1 Yes 2007-11-16 36.7
#> 6 PAL0708 6 Adelie… Anvers Torge… Adul… N3A2 Yes 2007-11-16 39.3
#> # … with 7 more variables: `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>, and
#> # abbreviated variable names ¹studyName, ²`Sample Number`, ³`Individual ID`,
#> # ⁴`Clutch Completion`, ⁵`Culmen Length (mm)`
#> # ℹ Use `colnames()` to see all variable names
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_l…¹ body_…² sex year
#> <fct> <fct> <dbl> <dbl> <int> <int> <fct> <int>
#> 1 Adelie Torgersen 39.1 18.7 181 3750 male 2007
#> 2 Adelie Torgersen 39.5 17.4 186 3800 fema… 2007
#> 3 Adelie Torgersen 40.3 18 195 3250 fema… 2007
#> 4 Adelie Torgersen NA NA NA NA NA 2007
#> 5 Adelie Torgersen 36.7 19.3 193 3450 fema… 2007
#> 6 Adelie Torgersen 39.3 20.6 190 3650 male 2007
#> # … with abbreviated variable names ¹flipper_length_mm, ²body_mass_g