Prepare attributes

Extract variableNames from data file(s) and add them to attributes.csv. The helper validate_file_paths can be used to create vectors of valid file paths that can be checked and then passed as data_path argument to prep_attributes.

Usage

prep_attributes(
  data_path = "data",
  attributes_path = file.path("data", "metadata", "attributes.csv"),
  ...
)

Arguments

data_path

character vector of either:

1. path(s) to the data file(s).

2. single path to directory containing data file(s). Currently only tabular .csv and .tsv files are supported. Alternatively attributes returned using names() can be extracted from r object, stored as .rds files.

attributes_path

path to the attributes.csv`` file. Defaults to data/metadata/attributes.csv`.

...

parameters passed to list.files(). For example, use recursive = TRUE to list files in a folder recursively or use pattern to filter files for patterns.

Value

prep_attributes() updates the attributes.csv and writes to attributes_path.

Examples

if (FALSE) { # \dontrun{
create_spice()
# extract attributes from all `csv`, `tsv`, `rds` files in the data folder
# (non recursive)
prep_attributes()
# recursive
prep_attributes(recursive = TRUE)
# extract attributes from a single file using file path
data_path <- system.file("example-dataset","BroodTables.csv",
                         package = "dataspice")
prep_attributes(data_path)
# extract attributes from a single file by file path pattern matching
data_path <- system.file("example-dataset", package = "dataspice")
prep_attributes(data_path, pattern = "StockInfo")
# extract from a folder using folder path
data_path <- system.file("example-dataset", package = "dataspice")
prep_attributes(data_path)
} # }