anonymity.tools.utils_k_anon package#
Submodules#
anonymity.tools.utils_k_anon.utils_k_anonymity module#
- anonymity.tools.utils_k_anon.utils_k_anonymity.clear_white_spaces(table: DataFrame) DataFrame #
Deletes any white spaces from column names.
- Parameters:
table (pandas dataframe) – dataframe with the data under study.
- Returns:
table which columns don’t contain whitespaces.
- Return type:
pandas dataframe
- anonymity.tools.utils_k_anon.utils_k_anonymity.create_ranges(data, range_step)#
- anonymity.tools.utils_k_anon.utils_k_anonymity.generalization(column: List | ndarray, hierarchies: dict, gen_level: int, name: str) List | ndarray | None #
Generalizes a column based on its data type.
- Parameters:
column (list of values) – column from the table under study that needs to be generalized.
hierarchies (dictionary) – hierarchies for generalization of string columns.
gen_level (int) – Current level of generalization of each of the columns of the table.
name (string) – Name of the column that needs to be generalized.
- Returns:
List of generalized values.
- Return type:
list of values
- anonymity.tools.utils_k_anon.utils_k_anonymity.string_to_interval(column: List | ndarray) List | ndarray #
Converts a string interval to an actual interval type, to facilitate the comparison of each data.
- Parameters:
column (list of strings) – List of intervals as strings.
- Returns:
List containing the intervals converted to the proper data type.
- Return type:
list of intervals
- anonymity.tools.utils_k_anon.utils_k_anonymity.suppress_identifiers(table: DataFrame, ident: List | ndarray) DataFrame #
Removes all the identifiers in the database.
- Parameters:
table (pandas dataframe) – dataframe with the data under study.
ident (list of strings) – list with the name of the columns of the dataframe that are identifiers.
- Returns:
table with the identifiers fully anonymized.
- Return type:
pandas dataframe