Construct a csv tabular data file and create metadata of type dataTable

create_dataTable writes a tabular data file of type csv and generates a EML entity of type dataTable

Usage

create_dataTable(
  dfname,
  description,
  dateRangeField = NULL,
  overwrite = FALSE,
  projectNaming = TRUE,
  missingValueCode = NULL,
  additional_information = NULL
)

Arguments

dfname: (character) The quoted or unquoted name of the R data frame or tibble.
description: (character) A quoted description of the data frame or tibble that will populate the entityDescription element of the EML document. name of the raster data to be processed is included as a parameter in this metadata file).
dateRangeField: (optional) (character) The quoted name of the data entity field that is a date field that would reflect the start and end dates of the data reflected in the data entity.
overwrite: (logical) A logical indicating whether to overwrite an existing file bearing the same name as csv file as it is imported.
projectNaming: (logical) Logical indicating if the resulting csv file should be renamed per the style used in the capeml ecosystem with the project id + base file name + file extension. If set to false, the resulting csv will bear the name the object in the R environment.
missingValueCode: (optional) (character) create_dataTable will automatically document the presence of NA and NaN entries as missing values in the EML output. The user has the ability to identify one additional indicator of missing values (e.g., "-9999", "missing").
additional_information: (character) Additional information about the data object. Should be quoted, and accepts (but does not require) markdown formatting.

Value

EML dataTable object is returned. Additionally, the data entity is written to file as type csv, and renamed with the package number + base file name + md5sum + file extension (csv in this case).

Details

create_dataTable writes a tabular data file of type csv and creates a corresponding EML dataTable object from a data frame or tibble object in the R environment. The function reads the attributes and classes contained within a supporting yaml file generated from write_attributes function - create_dataTable will look for a file in the working directory with a name of type data_object_name_attrs.yaml. Factors also are read from a supporting yaml file - create_dataTable will look for a file in the working directory with a name of type data_object_name_factors.yaml. If that exists, the factor details outlined in that file will be incorporated into the EML, else the EML will be built without factor metadata. Note that this functionality is predicated on the existence of a file containing metadata about any factors in the dataframe, that the file is in the working directory, and that the file matches the dataframe name precisely; the function does not look for variables of type factor in the dataframe. In addition to generating a EML entity of type dataTable, create_dataTable writes the R object to file as type csv, and renames the file with package number + base object name + file extension (csv in this case) if selected.

Note

If project naming is TRUE then create_dataTable will look for a package number (packageNum) in `config.yaml`; this parameter is not passed to the function and it must exist.

Examples

if (FALSE) { # \dontrun{

mycars <- mtcars |>
  head()

try({
  capeml::write_attributes(mycars)
  capeml::write_factors(mycars)
})

# create_dataTable with optional arguments dateRangeField and missingValueCode
mycars_DT <- capeml::create_dataTable(
 dfname      = mycars,
 description = "just a few cars",
 )

} # }