madshapR (version 2.0.0)

dossier_summarize: Generate an assessment report and summary of a dossier

Description

Assesses and summarizes the content and structure of a dossier (list of datasets) and generates reports of the results. This function can be used to evaluate data structure, presence of specific fields, coherence across elements, and data dictionary formats, and to summarize additional information about variable distributions and descriptive statistics.

Usage

dossier_summarize(
  dossier,
  group_by = NULL,
  taxonomy = NULL,
  valueType_guess = TRUE
)

Value

A list of data frames containing overall assessment reports and summaries grouped by dataset.

Arguments

dossier

List of data frame(s), each of them being datasets.

group_by

A character string identifying the column in the dataset to use as a grouping variable. Elements will be grouped by this column.

taxonomy

An optional data frame identifying a variable classification schema.

valueType_guess

Whether the output should include a more accurate valueType that could be applied to the dataset. TRUE by default.

Details

A dossier is a named list containing at least one data frame or more, each of them being datasets. The name of each data frame will be use as the reference name of the dataset.

A taxonomy is a classification schema that can be defined for variable attributes. A taxonomy is usually extracted from an Opal environment, and a taxonomy object is a data frame that must contain at least the columns taxonomy, vocabulary, and terms. Additional details about Opal taxonomies are available online.

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.

Examples

# \donttest{

# use madshapR_examples provided by the package
library(dplyr)

###### Example : a dataset list is a dossier by definition.
    
dataset1 <- as_dataset(madshapR_examples$`dataset_example` %>% group_by(pick('gndr')))
dataset2 <- as_dataset(madshapR_examples$`dataset_example - error`, col_id = "part_id")
dossier <- dossier_create(list(dataset1,dataset2))

summary_dossier <- dossier_summarize(dossier)
glimpse(summary_dossier)

# }