format_columns: Format and standardize column names and data types of an occurrence dataset

Description

Format and standardize column names and data types of an occurrence dataset

Usage

format_columns(
  occ,
  metadata,
  extract_binomial = TRUE,
  binomial_from = NULL,
  include_subspecies = FALSE,
  include_variety = FALSE,
  check_numeric = TRUE,
  numeric_columns = NULL,
  check_encoding = TRUE,
  data_source = NULL,
  progress_bar = FALSE,
  verbose = FALSE
)

Value

A data.frame with standardized column names and data types according to the specified metadata.

Arguments

occ: (data.frame or data.table) a dataset with occurrence records, preferably obtained from import_gbif(), get_specieslink(), get_bien(), or get_idigbio().
metadata: (character or data.frame) if a character, one of 'gbif', 'specieslink', 'bien', or 'idigbio', specifying which metadata template to use (the corresponding data frames are available in RuHere::prepared_metadata). If a data.frame is provided, it must have 21 columns (see Details).
extract_binomial: (logical) whether to create a column with the binomial name of the species. If FALSE, it will create a column "species" with the exact name stored in the scientificName column. Default is TRUE.
binomial_from: (character) the column name in metadata from which to extract the binomial name. Only applicable if extract_binomial = TRUE. If metadata corresponds to one of the predefined sources ('gbif', specieslink', 'bien', or 'idigbio'), predefined columns will be used automatically. Default is "scientificName".
include_subspecies: (logical) whether to include subspecies in the binomial name. Only applicable if extract_binomial = TRUE. If TRUE, the function includes any infraspecific epithet after the pattern "subsp.". Default if FALSE.
include_variety: (logical) whether to include variety in the binomial name. Only applicable if extract_binomial = TRUE. If TRUE, the function includes any infraspecific epithet after the pattern "var.". Default if FALSE.
check_numeric: (logical) whether to check and coerce the columns specified in numeric_columns to numeric type. Default is TRUE.
numeric_columns: (character) a vector of column names that must be numeric. Default is NULL, meaning that if check_numeric = TRUE, the following columns will be coerced: 'decimalLongitude', 'decimalLatitude', 'coordinateUncertaintyInMeters', 'elevation', and 'year'.
check_encoding: (logical) whether to check and fix the encoding of columns that typically contain special characters (see Details). Default is TRUE.
data_source: (character) the source of the occurrence records. Default is NULL, meaning it will use the same string provided in metadata. If metadata is a user-defined data.frame, this argument must be specified.
progress_bar: (logical) whether to display a progress bar during processing. If TRUE, the 'pbapply' package must be installed. Default is FALSE.
verbose: (logical) whether to print messages about the progress. Default is FALSE.

Details

If a user-defined metadata data.frame is provided, it must include the following 21 columns: 'scientificName', 'collectionCode', 'catalogNumber', 'decimalLongitude', 'decimalLatitude', 'coordinateUncertaintyInMeters', 'elevation', 'country', 'stateProvince', 'municipality', 'locality', 'year', 'eventDate', 'recordedBy', 'identifiedBy', 'basisOfRecord', 'occurrenceRemarks', 'habitat', 'datasetName', 'datasetKey', and 'key'.

If check_encoding = TRUE, the function will inspect and, if necessary, fix the encoding of these columns: 'collectionCode', 'catalogNumber', 'country', 'stateProvince', municipality', 'locality', 'eventDate','recordedBy', 'identifiedBy', 'basisOfRecord', and 'datasetName'.

Examples

Run this code

# Example with GBIF
data("occ_gbif", package = "RuHere") #Import data example
gbif_standardized <- format_columns(occ_gbif, metadata = "gbif")
# Example with SpeciesLink
data("occ_splink", package = "RuHere") #Import data example
splink_standardized <- format_columns(occ_splink, metadata = "specieslink")
# Example with BIEN
data("occ_bien", package = "RuHere") #Import data example
bien_standardized <- format_columns(occ_bien, metadata = "bien")
# Example with idigbio
data("occ_idig", package = "RuHere") #Import data example
idig_standardized <- format_columns(occ_idig, metadata = "idigbio")

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