piper.verbs.duplicate_names¶
-
piper.verbs.duplicate_names(columns: List, sep: str = '_', info: bool = True) → List[source]¶ identify and de-duplicate dataframe column names
Examples
cols = [ 'duplicate', 'allocated', 'first_name', 'last_name', 'employee_status', 'last_name', 'subject', 'hire_date', 'allocated', 'full_time?', 'certification', 'certification', 'certification', 'certification' ] expected = [ 'duplicate', 'allocated', 'first_name', 'last_name', 'employee_status', 'last_name_1', 'subject', 'hire_date', 'allocated_1', 'full_time?', 'certification', 'certification_1', 'certification_2', 'certification_3' ] df = pd.DataFrame(None, columns=cols) assert expected == duplicate_names(df.columns.tolist())
- Parameters
sep – default ‘_’. Separator used to append suffix number for duplicate column name values.
- Returns
- Return type
column names