data_dict_update: Update a data dictionary from a dataset

Description

Updates a data dictionary from a dataset, creating a new data dictionary with updated content, from variables selected in the dataset. Any previous other meta data will be preserved. The new data dictionary can be applied to the dataset using data_dict_apply().

Usage

data_dict_update(data_dict = NULL, dataset, cols = names(dataset))

Value

A list of data frame(s) identifying a data dictionary.

Arguments

data_dict: A list of data frame(s) representing metadata of the input dataset. Automatically generated if not provided.
dataset: A dataset object.
cols: An optional character string specifying the name(s) or position(s) of the column(s) for which meta data will be updated. All by default.

Details

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.

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.

Examples

Run this code

{

library(dplyr)

# use madshapR_examples provided by the package
dataset   <- madshapR_examples$`dataset_example`
data_dict <- as_data_dict_mlstr(madshapR_examples$`data_dictionary_example`)
dataset <- data_dict_apply(dataset,data_dict)

# the data dictionary contains no categorical variable.

# create a category in the dataset
dataset   <- dataset %>% mutate(gndr = as_category(gndr, labels = c("coucou" = 1),na_values = 2))
new_data_dict <- data_dict_update(data_dict, dataset, "gndr")

head(dataset)

}