new_file_collection: Create a list of file_definitionuration objects
In a-maldet/readall: Read FWF, DSV, EXCEL And SAS Files

Description Usage Arguments Value File types difference file_structure/file_definition/file_collection adapters

With the function read_data() you can read FWF-, DSV-, EXCEL- or SAS data files and store the data in a data.frame. But with read_data() you can also read multiple data files at once and automatically concatenate the resulting data.frames into a single data.frame. In order to do so, you need to create a list of [file_definition class][new_file_definition()] objects. This file_definitionuration list is a file_collection class object and each list entry a file_definition class class object holding all information needed for reading a specific data file. Each file_definitionuration list entry can be created by using one of the following functions:

new_file_definition() for FWF, DSV or EXCEL data files
new_file_definition_fwf() for FWF data files
new_file_definition_dsv() for DSV data files
new_file_definition_excel() for EXCEL data files
new_file_definition_sas() for SAS data files

new_file_collection(
  ...,
  to_lower = NULL,
  cols_keep = NULL,
  extra_col_file_path = NULL,
  extra_adapters = new_adapters()
)

`...`	Multiple file file_definitionurations. This file file_definitionurations can be created with the functions `new_file_definition()`, `new_file_definition_fwf()`, `new_file_definition_dsv()`, `new_file_definition_excel()` or `new_file_definition_sas()` depending on the given file type.
`to_lower`	An optional logical argument. If omitted, then the `to_lower` arguments in the file_definitionurations given in `...` remain unchanged. If `to_lower` is not omitted, then for each file_definitionuration the argument `to_lower` will be updated with the new value. The `to_lower` argument defines if the names of the columns should be transformed to lower case after reading the data set (by calling `read_data()`). This transformation will be applied before comparing the column names (in the case of SAS-Files or DSV- and EXCE-Files with `header = TRUE`).
`cols_keep`	An optional argument, which can either be `TRUE` or a character vector. If the argument is omitted (`NULL`), then the `cols_keep` arguments of all `file_collection` entries will stay unchanged. If the argument `cols_keep` is not `NULL`, then its value will overwrite the `cols_keep` argument of each `file_collection` entry. If the `cols_keep` argument is set to `TRUE`, then all columns of each data set will be kept when calling `read_data()`. If `cols_keep` is a character vector, then the values in `cols_keep` represent the names of the columns, which will be kept, when calling `read_data()`.
`extra_col_file_path`	An optional argument, which can either be `FALSE` or a string. If the argument is omitted (`NULL`), then the `extra_col_file_path` argument of each `file_collection` entry will stay unchanged. If the argument `extra_col_file_path` is not `NULL`, then its value will overwrite the `extra_col_file_path` argument of each `file_collection` entry. If set to `FALSE` no file-path-column will be added to the data sets, when calling `read_data()`. If the argument `extra_col_file_path` is a string, then a column holding the file path of each data file will be added to the read data sets, when calling `read_data()`. The string of `extra_col_file_path` will be used as column name for this additional column.
`extra_adapters`	An optional adapters class object, which holds a list of adapter functions. These adapter functions will be added to the adapter functions already stored in each file file_definitionuration passed in via `...`. For further details on adapter functions see section adapters.

A list, where each list entry is file file_definitionuration, which holds all information needed to read a specific data file with the function read_data().

The function read_data() can read read four different types of data

FWF: Fixed width files. This files are text files, where the data is stored in columns, that have a fixed character width.
DSV: Delimiter-separated value file. This files are text files, where the data is stored in columns that are separated by a delimiter character.
EXCEL: An excel file holding the data.
SAS: A SAS file holding the data.

In order to read a data file with the function read_data(), it is useful to create a file_definitionuration or file_structure class object, holding all needed data file file_structures:
- new_file_definition_fwf() or new_file_structure_fwf() for FWF files
- new_file_definition_dsv() or new_file_structure_dsv() for DSV files
- new_file_definition_excel() or new_file_structure_excel() for Excel files
- new_file_definition_sas() or new_file_structure_sas() for SAS files

The goal of the package readall is it to read data files. For this purpose the package offers three different class objects in order to store meta data about the data files:

file_structure class objects: Objects of this class can be used in order to define all file type specific information (e.g. column positions, column names, column types, deliminator symbols, rows to skip etc.). The idea is, that one file_structure object may valid for several files and therefore be used to read multiple data files.
file_definition class objects: Objects of this class type contain all informations in order to read a single specific data file (path to the data file, file file_structure etc.). A file_definition class object contains a file_structure, which holds all file type specific information, but also other informations that are only valid for this specific file.
file_collection class objects: A file_collection class object is simply a list holding multiple file_definition class objects. A file_collection class object can be used in order to read several data files at once and concatenate the data into a single data.frame.

An adapter function is a function that takes a data.frame as input argument and returns a modified version of this data.frame. The adapter functions are stored in an adapters class object, which is a special list that contains all adapter functions and a description text of each function. This class objects can be created by using the function new_adapters(). The adapters class objects can be added to a file_structure or a file_definition or a file_collection class object. After reading a data file (by calling read_data(file_definition)) all adapter functions listed in the adapters argument of the file_definition]new_file_definition() class object will be applied consecutively to the loaded data set. Adapter functions can be added to an existing file_structure or a file_definition or a file_collection class object by using the function add_adapters(). Adapter functions can be used for several tasks:

adapt the data sets in such a way that they can be concatenated for mutliple years
compute new variables from existing variables
fix errors in variables
transform the values of a variable of an older data set, such that it complies with a newer variable definition

adapt the data sets in such a way that they can be concatenated for mutliple years
compute new variables from existing variables
fix errors in variables
transform the values of a variable of an older data set, such that it complies with a newer variable definition