R/04-catalogue_functions.R
valueType_self_adjust.RdDetermines the valueType of an object based on base::typeof() and
base::class().
The possible values returned are 'date', 'boolean', 'integer', 'decimal', and
'text'.
valueType_self_adjust(...)Object that can be either a dataset or a data dictionary.
Either a data frame, identifying the dataset, or a list of data frame(s) identifying a data dictionary, depending which the input refers to.
A data dictionary contains the list of variables in a dataset and metadata
about the variables and can be associated with a dataset. A data dictionary
object is a list of data frame(s) named 'Variables' (required) and
'Categories' (if any). To be usable in any function, the data frame
'Variables' must contain at least the name column, with all unique and
non-missing entries, and the data frame 'Categories' must contain at least
the variable and name columns, with unique combination of
variable and name.
A dataset is a data table containing variables. A dataset object is a data frame and can be associated with a data dictionary. If no data dictionary is provided with a dataset, a minimum workable data dictionary will be generated as needed within relevant functions. Identifier variable(s) for indexing can be specified by the user. The id values must be non-missing and will be used in functions that require it. If no identifier variable is specified, indexing is handled automatically by the function.
The valueType is a declared property of a variable that is required in certain functions to determine handling of the variables. Specifically, valueType refers to the OBiBa data type of a variable. The valueType is specified in a data dictionary in a column 'valueType' and can be associated with variables as attributes. Acceptable valueTypes include 'text', 'integer', 'decimal', 'boolean', datetime', 'date'. The full list of OBiBa valueType possibilities and their correspondence with R data types are available using valueType_list. The valueType can be used to coerce the variable to the corresponding data type.
{
###### Example : The valueType of a dataset can be adjusted. each column is
# evaluated as whole, and the best valueType match found is applied. If
# there is no better match found, the column is left as it is.
head(valueType_self_adjust(mtcars['cyl']))
}
#> # A tibble: 6 × 1
#> cyl
#> <int>
#> 1 6
#> 2 6
#> 3 4
#> 4 6
#> 5 8
#> 6 6