[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:def add_datepart(df, fldname, drop=True, time=False):\n    "Helper function that adds columns relevant to a date."\n    fld = df[fldname]\n    fld_dtype = fld.dtype\n    if isinstance(fld_dtype, pd.core.dtypes.dtypes.DatetimeTZDtype):\n        fld_dtype = np.datetime64\n\n    if not np.issubdtype(fld_dtype, np.datetime64):\n        df[fldname] = fld = pd.to_datetime(fld, infer_datetime_format=True)\n    targ_pre = re.sub(\'[Dd]ate$\', \'\', fldname)\n    attr = [\'Year\', \'Month\', \'Week\', \'Day\', \'Dayofweek\', \'Dayofyear\',\n            \'Is_month_end\', \'Is_month_start\', \'Is_quarter_end\', \'Is_quarter_start\', \'Is_year_end\', \'Is_year_start\']\n    if time: attr = attr + [\'Hour\', \'Minute\', \'Second\']\n    for n in attr: df[targ_pre + n] = getattr(fld.dt, n.lower())\n    df[targ_pre + \'Elapsed\'] = fld.astype(np.int64) // 10 ** 9\n    if drop: df.drop(fldname, axis=1, inplace=True)\''}, {'role': 'assistant', 'content': "['data_preprocessing']"}]