def calc(carg): # calculate the actual result carg = carg.astype(object) parsed = parsing.try_parse_year_month_day(carg / 10000, carg / 100 % 100, carg % 100) return tslib.array_to_datetime(parsed, errors=errors)
def parse_date_fields(year_col, month_col, day_col): """ Parse columns with years, months and days into a single date column. .. deprecated:: 1.2 """ warnings.warn( """ Use pd.to_datetime({"year": year_col, "month": month_col, "day": day_col}) instead to get a Pandas Series. Use ser = pd.to_datetime({"year": year_col, "month": month_col, "day": day_col}) and np.array([s.to_pydatetime() for s in ser]) instead to get a Numpy array. """, # noqa: E501 FutureWarning, stacklevel=find_stack_level(), ) year_col = _maybe_cast(year_col) month_col = _maybe_cast(month_col) day_col = _maybe_cast(day_col) return parsing.try_parse_year_month_day(year_col, month_col, day_col)
def parse_date_fields(year_col, month_col, day_col): year_col = _maybe_cast(year_col) month_col = _maybe_cast(month_col) day_col = _maybe_cast(day_col) return parsing.try_parse_year_month_day(year_col, month_col, day_col)