valueType_adjust: Attribute the valueType from a data dictionary to a dataset,...

In madshapR: Support Technical Processes Following 'Maelstrom Research' Standards

Attribute the valueType from a data dictionary to a dataset, or vice versa

Description

Takes the valueType of the input (from) and attributes it to the output (to). The parameters 'from' and 'to' can be either a dataset or a data dictionary. Depending on the input provided, the valueType replaced is either in the 'valueType' column of a data dictionary or cast to a column in a dataset. If 'to' is not provided, the function calls valueType_self_adjust() instead. The possible values returned are 'date', 'boolean', 'integer', 'decimal', and text'.

Usage

valueType_adjust(from, to = NULL)

Arguments

from	Object to be adjusted. Can be either a dataset or a data dictionary.
to	Object to be adjusted. Can be either a dataset or a data dictionary. NULL by default.

Details

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.

Value

Either a data frame, identifying the dataset, or a list of data frame(s) identifying a data dictionary, depending which is 'to'.

See Also

valueType_self_adjust()

Examples

{

# use madshapR_DEMO provided by the package
library(dplyr)

dataset <- madshapR_DEMO$dataset_TOKYO[c(1:4),'prg_ever']
data_dict <-
  madshapR_DEMO$data_dict_TOKYO %>%
  data_dict_filter(filter_var = 'name == "prg_ever"') %>%
  as_data_dict_mlstr()

head(valueType_adjust(from = data_dict,to = dataset))

}

madshapR documentation built on May 29, 2024, 7:43 a.m.