Skip to contents

Constructor for ea_data Objects

Source: R/ea_data_class.R
ea_data.Rd

Creates an ea_data object from a data frame and associated metadata. This function serves as the primary constructor for the ea_data-class. It validates the presence and type of required columns, standardizes the value column name to value, and stores metadata in the meta slot.

Usage

ea_data(
  data,
  value_col,
  data_type,
  region,
  location_descriptor,
  units,
  species = NA_character_,
  source_citation = "No citation provided",
  ...
)

# S4 method for class 'data.frame,character'
ea_data(
  data,
  value_col,
  data_type,
  region,
  location_descriptor,
  units,
  species = NA_character_,
  source_citation = "No citation provided",
  ...
)

Arguments

data

A data.frame containing at least a year column and a numeric column specified by value_col.

value_col

A list naming the column(s) in data that contains the numeric values to be marked as columns with names appended '_value'

data_type

A character string describing the type of data (e.g., "temperature").

region

A character string indicating the geographic region.

location_descriptor

A character string describing the location (e.g., "bottom", "surface").

units

A character string indicating the units of measurement.

species

[character(1)] Optional. A character string naming the species (default is NA_character_).

source_citation

[character(1)] Optional. A character string providing the data source citation.

...

Additional metadata fields to be stored in the meta slot as a named list.

Value

An object of class ea_data.

Examples

df <- data.frame(year = 2000:2005, temp_c = rnorm(6))
obj <- ea_data(df,
  value_col = c("temp_c"),
  data_type = "temperature",
  region = "Scotian Shelf",
  location_descriptor = "bottom",
  units = "°C",
  project = "AZMP"
)

# Access metadata
obj[["region"]]
#> [1] "Scotian Shelf"

# Access data
obj[["data"]]
#> # A tibble: 6 × 2
#>    year temp_c_value
#>   <int>        <dbl>
#> 1  2000       1.89  
#> 2  2001      -0.0974
#> 3  2002      -0.936 
#> 4  2003      -0.0160
#> 5  2004      -0.827 
#> 6  2005      -1.51