Functions to Support Data Management and Processing Using the Maelstrom Research Approach
Validate and coerce any object as a categorical variable.
Validate and coerce any object as an Opal data dictionary format
Validate and coerce any object as a workable data dictionary structure
Validate and coerce any object as a data dictionary
Validate and coerce any object as a dataset
Validate and coerce any object as a dossier (list of dataset(s))
Validate and coerce any object as a taxonomy
Validate and coerce any object according to a given valueType
Objects exported from other packages
Objects exported from other packages
Objects exported from other packages
Assess a data dictionary for potential issues in categories
Assess categorical variables for non-Boolean values in 'missing' colum...
Assess a data dictionary for non-valid valueType values
Assess a data dictionary for potential issues in variables
Assess a data dictionary and associated dataset for category differenc...
Assess a data dictionary and associated dataset for valueType differen...
Assess a data dictionary and associated dataset for undeclared variabl...
Assess variable names in a data dictionary for non-standard formats
Return the id column names(s) of a dataset
Apply a data dictionary to a dataset
Transform multi-row category column(s) to single rows and join to "Var...
Generate an assessment report for a data dictionary
Transform single-row category information to multiple rows as element
Generate a data dictionary from a dataset
Subset data dictionary by row values
Group listed data dictionaries by specified column names
Split grouped data dictionaries into a named list
Bind listed data dictionaries
Inner join between a dataset and its associated data dictionary
Transform column(s) of a data dictionary from wide format to long form...
Transform column(s) of a data dictionary from long format to wide form...
Add shortened labels to data dictionary
Ungroup data dictionary
Update a data dictionary from a dataset
Create an empty dataset from a data dictionary
Apply data dictionary category labels to the associated dataset variab...
Generate an assessment report for a dataset
Generate an evaluation of all variable values in a dataset
Generate an assessment report and summary of a dataset
Generate a web-based visual report for a dataset
Remove labels (attributes) from a data frame, leaving its unlabelled c...
Generate a dossier from a list of one or more datasets
Generate an assessment report of a dossier
Generate an assessment report and summary of a dossier
Validate and coerce any object as a non-categorical variable.
Get the first label from a data dictionary
Test if an object has categorical variables.
Test and validate if an object is a categorical variable.
Test if an object is a valid Maelstrom data dictionary
Test if an object is a workable data dictionary structure
Test if an object is a valid data dictionary
Test if an object is a valid dataset
Test if an object is a valid dossier (list of dataset(s))
Test if an object is a valid taxonomy
Test if a character object is one of the valid valueType values
Call to online documentation
madshapR: Functions to Support Data Management and Processing Using th...
Provide descriptive statistics for variables of categorical in a datas...
Provide descriptive statistics for variables of type 'date' in a datas...
Provide descriptive statistics for variables of type 'datetime' in a d...
Provide descriptive statistics for variables of type 'numeric' in a da...
Provide descriptive statistics for variables of type 'text' in a datas...
Provide descriptive statistics for variables in a dataset
Convert typeof (and class if any) into its corresponding valueType
Attribute the valueType from a data dictionary to a dataset, or vice v...
Convert valueType into its corresponding typeof and class in R represe...
Guess the first possible valueType of an object (Can be a vector)
Return the valueType of an object
Self-adjust the valueType from a data dictionary or a dataset.
Generate a list of charts, figures and summary tables of a variable
Functions to support data cleaning, evaluation, and description, developed for integration with Maelstrom Research software tools. 'madshapR' provides functions primarily to evaluate and manipulate datasets and data dictionaries in preparation for data harmonization with the package 'Rmonize' and to facilitate integration and transfer between RStudio servers and secure Opal environments. 'madshapR' functions can be used independently but are optimized in conjunction with ‘Rmonize’ functions for streamlined and coherent harmonization processing.
Useful links