data_dict_filter: Subset data dictionary by row values

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

Subset data dictionary by row values

Description

Subsets either or both the 'Variables' and 'Categories' elements of a data dictionary. Rows are conserved if their values satisfy the condition. This is a wrapper function analogous to dplyr::filter().

Usage

data_dict_filter(
  data_dict,
  filter_var = NULL,
  filter_cat = NULL,
  filter_all = NULL
)

Arguments

data_dict	A list of data frame(s) representing metadata to be filtered.
filter_var	Expressions that are defined in the element 'Variables' in the data dictionary.
filter_cat	Expressions that are defined in the element 'Categories' in the data dictionary.
filter_all	Expressions that are defined both in the 'Categories' and 'Variables' in the data dictionary.

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.

Value

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

See Also

dplyr::filter()

Examples

{

# use madshapR_DEMO provided by the package

# Create a list of data dictionaries where the column 'table' is added to 
# refer to the associated dataset. The object created is not a 
# data dictionary per say, but can be used as a structure which can be 
# shaped into a data dictionary.
library(dplyr)

data_dict_list <- list(
  data_dict_1 <- madshapR_DEMO$data_dict_TOKYO ,
  data_dict_2 <- madshapR_DEMO$data_dict_MELBOURNE)
names(data_dict_list) = c("dataset_TOKYO","dataset_MELBOURNE")

data_dict_nest <- data_dict_list_nest(data_dict_list, name_group = 'table')

###### Example 1 search and filter through a column in 'Variables' element
data_dict_filter(data_dict_nest,filter_var = "valueType == 'text'")

###### Example 2 search and filter through a column in 'Categories' element
data_dict_filter(data_dict_nest,filter_cat = "missing == TRUE")

###### Example 3 search and filter through* a column in 'Variables' element.
# The column must exist in both 'Variables' and 'Categories' and have the
# same meaning
data_dict_filter(data_dict_nest,filter_all = "table == 'dataset_TOKYO'")

}

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