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Extract species x traits information from long format data

Source: R/fb_format_species_traits.R
fb_format_species_traits.Rd

Convert a flat data.frame with traits values for different species into a proper data.frame object that can then be used by other functions. The final output contains species in rows and traits in columns.

Usage

fb_format_species_traits(data, species, traits)

Arguments

data

a data.frame in a long format (see example).

species

a character of length 1. Name of the column with species names.

traits

a character of length >= 1. Name(s) of trait column(s).

Value

A data.frame with species in rows and traits in columns, with the first column names "species" containing the species names.

Examples

filename <- system.file(
  "extdata", "woodiv_raw_data.csv", package = "funbiogeo"
)
all_data <- read.csv(filename)

head(all_data)
#>       site  country longitude latitude species count       family     genus
#> 1 26351755 Portugal   2635000  1755000    JPHO     1 Cupressaceae Juniperus
#> 2 26351755 Portugal   2635000  1755000    PPIR     1     Pinaceae     Pinus
#> 3 26351765 Portugal   2635000  1765000    JPHO     1 Cupressaceae Juniperus
#> 4 26351955 Portugal   2635000  1955000    JPHO     1 Cupressaceae Juniperus
#> 5 26351955 Portugal   2635000  1955000    PPIR     1     Pinaceae     Pinus
#> 6 26351965 Portugal   2635000  1965000    JPHO     1 Cupressaceae Juniperus
#>              binomial endemism cultivated plant_height seed_mass      sla
#> 1 Juniperus phoenicea        0          0      4.88150  79.86000 4.365246
#> 2      Pinus pinaster        0          0     19.75384  55.83434 3.357539
#> 3 Juniperus phoenicea        0          0      4.88150  79.86000 4.365246
#> 4 Juniperus phoenicea        0          0      4.88150  79.86000 4.365246
#> 5      Pinus pinaster        0          0     19.75384  55.83434 3.357539
#> 6 Juniperus phoenicea        0          0      4.88150  79.86000 4.365246
#>   wood_density
#> 1    0.6487500
#> 2    0.4430277
#> 3    0.6487500
#> 4    0.6487500
#> 5    0.4430277
#> 6    0.6487500

traits <- c("plant_height", "seed_mass", "sla", "wood_density")

species_traits <- fb_format_species_traits(all_data, "species", traits)
head(species_traits)
#>   species plant_height seed_mass      sla wood_density
#> 1    AALB     49.64162 67.866923 7.483978    0.4490821
#> 2    ACEP     25.87500 64.703750       NA           NA
#> 3    ANEB     15.00000        NA 3.420603           NA
#> 4    APIN     27.33333 55.520000 3.420603    0.4586508
#> 5    CLIB     35.63636 86.872600       NA    0.4500000
#> 6    CSEM     24.69231  7.608125 5.824112    0.5184729