| as_category | Validate and coerce any object as a categorical variable. | 
| as_dataset | Validate and coerce any object as a dataset | 
| as_data_dict | Validate and coerce any object as a data dictionary | 
| as_data_dict_mlstr | Validate and coerce any object as an Opal data dictionary format | 
| as_data_dict_shape | Validate and coerce any object as a workable data dictionary structure | 
| as_dossier | Validate and coerce any object as a dossier (list of dataset(s)) | 
| as_taxonomy | Validate and coerce any object as a taxonomy | 
| as_valueType | Validate and coerce any object according to a given valueType | 
| bookdown_open | Objects exported from other packages | 
| bookdown_render | Objects exported from other packages | 
| bookdown_template | Objects exported from other packages | 
| check_dataset_categories | Assess a data dictionary and associated dataset for category differences | 
| check_dataset_valueType | Assess a data dictionary and associated dataset for valueType differences | 
| check_dataset_variables | Assess a data dictionary and associated dataset for undeclared variables | 
| check_data_dict_categories | Assess a data dictionary for potential issues in categories | 
| check_data_dict_missing_categories | Assess categorical variables for non-Boolean values in 'missing' column | 
| check_data_dict_valueType | Assess a data dictionary for non-valid valueType values | 
| check_data_dict_variables | Assess a data dictionary for potential issues in variables | 
| check_name_standards | Assess variable names in a data dictionary for non-standard formats | 
| color_palette_maelstrom | Built-in data frame of colors used in the graphs and charts. | 
| col_id | Return the id column names(s) of a dataset | 
| dataset_cat_as_labels | Apply data dictionary category labels to the associated dataset variables | 
| dataset_evaluate | Generate an assessment report for a dataset | 
| dataset_preprocess | Generate an evaluation of all variable values in a dataset | 
| dataset_summarize | Generate an assessment report and summary of a dataset | 
| dataset_visualize | Generate a web-based visual report for a dataset | 
| dataset_zap_data_dict | Remove labels (attributes) from a data frame, leaving its unlabelled columns | 
| data_dict_apply | Apply a data dictionary to a dataset | 
| data_dict_collapse | Transform multi-row category column(s) to single rows and join to "Variables" | 
| data_dict_evaluate | Generate an assessment report for a data dictionary | 
| data_dict_expand | Transform single-row category information to multiple rows as element | 
| data_dict_extract | Generate a data dictionary from a dataset | 
| data_dict_filter | Subset data dictionary by row values | 
| data_dict_group_by | Group listed data dictionaries by specified column names | 
| data_dict_group_split | Split grouped data dictionaries into a named list | 
| data_dict_list_nest | Bind listed data dictionaries | 
| data_dict_match_dataset | Inner join between a dataset and its associated data dictionary | 
| data_dict_pivot_longer | Transform column(s) of a data dictionary from wide format to long format | 
| data_dict_pivot_wider | Transform column(s) of a data dictionary from long format to wide format | 
| data_dict_trim_labels | Add shortened labels to data dictionary | 
| data_dict_ungroup | Ungroup data dictionary | 
| data_dict_update | Update a data dictionary from a dataset | 
| data_extract | Create an empty dataset from a data dictionary | 
| dossier_create | Generate a dossier from a list of one or more datasets | 
| dossier_evaluate | Generate an assessment report of a dossier | 
| dossier_summarize | Generate an assessment report and summary of a dossier | 
| drop_category | Validate and coerce any object as a non-categorical variable. | 
| first_label_get | Get the first label from a data dictionary | 
| has_categories | Test if an object has categorical variables. | 
| is_category | Test and validate if an object is a categorical variable. | 
| is_dataset | Test if an object is a valid dataset | 
| is_data_dict | Test if an object is a valid data dictionary | 
| is_data_dict_mlstr | Test if an object is a valid Maelstrom data dictionary | 
| is_data_dict_shape | Test if an object is a workable data dictionary structure | 
| is_dossier | Test if an object is a valid dossier (list of dataset(s)) | 
| is_taxonomy | Test if an object is a valid taxonomy | 
| is_valueType | Test if a character object is one of the valid valueType values | 
| madshapR_examples | Built-in material allowing the user to test the package with example data | 
| madshapR_website | Call to online documentation | 
| summary_variables | Provide descriptive statistics for variables in a dataset | 
| summary_variables_categorical | Provide descriptive statistics for variables of categorical in a dataset | 
| summary_variables_date | Provide descriptive statistics for variables of type 'date' in a dataset | 
| summary_variables_datetime | Provide descriptive statistics for variables of type 'datetime' in a dataset | 
| summary_variables_numeric | Provide descriptive statistics for variables of type 'numeric' in a dataset | 
| summary_variables_text | Provide descriptive statistics for variables of type 'text' in a dataset | 
| typeof_convert_to_valueType | Convert typeof (and class if any) into its corresponding valueType | 
| valueType_adjust | Attribute the valueType from a data dictionary to a dataset, or vice versa | 
| valueType_convert_to_typeof | Convert valueType into its corresponding typeof and class in R representation | 
| valueType_guess | Guess the first possible valueType of an object (Can be a vector) | 
| valueType_list | Built-in data frame of allowed valueType values | 
| valueType_of | Return the valueType of an object | 
| valueType_self_adjust | Self-adjust the valueType from a data dictionary or a dataset. | 
| variable_visualize | Generate a list of charts, figures and summary tables of a variable |