prep_dataset: Prep a dataset by removing variables, remove incomplete...
In BigelowLab/calanusthreshold: calanusthreshold

prep_dataset

R Documentation

Prep a dataset by removing variables, remove incomplete cases, aggregating specified columns, and applying threshold/labeling to the aggregated column

Description

Prep a dataset by removing variables, remove incomplete cases, aggregating specified columns, and applying threshold/labeling to the aggregated column

Usage

prep_dataset(
  x = read_dataset(),
  complete_cases_only = TRUE,
  lump_var = "Calanus finmarchicus",
  lump_fun = dplyr::starts_with,
  drop_var = c("geometry", "longitude", "latitude", "station", "year", "siconc",
    "sithick", complement_species(lump_var)),
  drop_fun = dplyr::starts_with,
  log_var = c("bathymetry", "chlor_a"),
  newname = "patch",
  threshold = 10000
)

Arguments

`x`	tibble of input data
`complete_cases_only`	logical, if TRUE drop incomplete records (after deselection)
`lump_var`	character character, vector of variables to sum into a new column
`lump_fun`	function, such as `starts_with`
`drop_var`	character, the variables to deselect
`drop_fun`	function, such as `starts_with`
`log_var`	character, variables to log scale (base 10), match with `any_of`
`newname`	character the name of the new aggregated colum
`threshold`	numeric, the threshold(s) used to define patches