get_datavyu_info: Scans a directory for datavyur exported '.csv' data.
In iamamutt/datavyur: Working with 'Datavyu' Data

Description Usage Arguments Details Value

The function will find data exported from .opf to .csv using the built-in Ruby script.

get_datavyu_info(
  folder = NULL,
  columns = NULL,
  files = NULL,
  class_overwrite = NULL,
  traverse = FALSE
)

`folder`	Either a scalar character pointing to a directory where contents are to be scanned, or a vector of `.csv` files to import instead of all the contents found within a folder. Defaults to the R option `datavyur.folder`, which is the internal example data folder that is used throughout this package. If `folder` is a character vector of multiple `.csv` file paths, set `as_list=TRUE`.
`columns`	Similar to the `files` argument. The name of the Datavyu "column" to import, as used in the original datavyu `.opf` file.
`files`	The short name of the Datavyu "file" to import, as used for the original datavyu `.opf` file name. For example, a Datavyu file `dyad1.opf`, when exported using `datavyu2csv.rb`, will have in the `.csv` file `dyad1` as the value in the column "file", and if `files="dyad1"` is specified for a function, only data from `dyad1.opf` will be imported even though they may be separated as multiple `.csv` files in a folder.
`class_overwrite`	A `list` of new classes to override the guessed classes when reading in `.csv` data. See `colClasses` from `data.table::fread()`. Sometimes `fread` doesn't get the class of the imported column right. This can happen if you have "codes" in your data that can be several possible types. Use `class_overwrite` to override improper type settings.
`traverse`	Search subfolders of `folder` for datavyur `.csv` files.

Most functions in this package only work if you had previously used the datavyu2csv.rb script to export a Datavyu file to .csv. This script can be obtained from ruby_script_folder(). Exported data is in the form of several "/column__file.csv" files. Files will be searched based on the directory supplied to the folder argument. Valid files will have the following columns: file, column, onset, offset, ordinal, along with custom user codes as columns.

data.frame with all info from the located .csv files consisting of the following columns:

column: the name of the specific column taken the .opf file.
codes: the argument/fields used to label each type of code in a column.
file: the file name taken from the original .opf file.
local: the path to the .csv file found on disk.
classes: the type for the given code.
combined: the column.field string to distinguish variable names.
old_classes: the estimated classes for each argument/field based on data.table's fread.