Support Technical Processes Following 'Maelstrom Research'
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Documentation for package ‘madshapR’ version 1.1.0
Help Pages
| 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 |
| 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_ungroup | Ungroup data dictionary |
| 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. |
| is_category | Test if an object is a valid dataset |
| 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_DEMO | Built-in material allowing the user to test the package with demo 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 |
| valueType_adjust | Attribute the valueType from a data dictionary to a dataset, or vice versa |
| 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 | Guess and attribute the valueType of a data dictionary or dataset variable |
| variable_visualize | Generate a list of charts, figures and summary tables of a variable |