code: def describe(
      data: Union[np.ndarray, pd.Series, pd.DataFrame],
      stats: Sequence[str] = None,
      *,
      numeric: bool = True,
      categorical: bool = True,
      alpha: float = 0.05,
      use_t: bool = False,
      percentiles: Sequence[Union[int, float]] = PERCENTILES,
      ntop: bool = 5,
  ) -> pd.DataFrame:
      return Description(
          data,
          stats,
          numeric=numeric,
          categorical=categorical,
          alpha=alpha,
          use_t=use_t,
          percentiles=percentiles,
          ntop=ntop,
      ).frame
  
imports: from statsmodels.compat.pandas import PD_LT_2, Appender, is_numeric_dtype
  from statsmodels.compat.scipy import SP_LT_19
  from typing import Union
  from collections.abc import Sequence
  import numpy
  import pandas
  from scipy import stats
  from statsmodels.iolib.table import SimpleTable
  from statsmodels.stats.stattools import jarque_bera
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.tools.docstring import Docstring, Parameter
  from statsmodels.tools.validation import array_like, bool_like, float_like, int_like
label_desc: Use image node_id 11 for calling a global function with example usage: describe(data, stats) and returns: Description