code: def add_margins(
      df: pd.DataFrame,
      vars: tuple[list[str], list[str]],
      margins: bool | list[str] = True,
  ) -> pd.DataFrame:
      """
      Add margins to a data frame.
  
      All margining variables will be converted to factors.
  
      Parameters
      ----------
      df : dataframe
          input data frame
  
      vars : list
          a list of 2 lists | tuples vectors giving the
          variables in each dimension
  
      margins : bool | list
          variable names to compute margins for.
          True will compute all possible margins.
      """
      margin_vars = _margins(vars, margins)
      if not margin_vars:
          return df
  
      # create margin dataframes
      margin_dfs = [df]
      for vlst in margin_vars[1:]:
          dfx = df.copy()
          for v in vlst:
              dfx.loc[0:, v] = "(all)"
          margin_dfs.append(dfx)
  
      merged = pd.concat(margin_dfs, axis=0)
      merged.reset_index(drop=True, inplace=True)
  
      # All margin columns become categoricals. The margin indicator
      # (all) needs to be added as the last level of the categories.
      categories = {}
      for v in itertools.chain(*vars):
          col = df[v]
          if not isinstance(df[v], pd.Categorical):
              col = pd.Categorical(df[v])
          categories[v] = col.categories
          if "(all)" not in categories[v]:
              categories[v] = categories[v].insert(
                  len(categories[v]), "(all)"
              )
  
      for v in merged.columns.intersection(list(categories.keys())):
          merged[v] = merged[v].astype(
              pd.CategoricalDtype(categories[v])
          )
  
      return merged
  
imports: from __future__ import annotations
  import inspect
  import itertools
  import warnings
  from collections import defaultdict
  from collections.abc import Iterable, Sequence
  from contextlib import suppress
  from typing import TYPE_CHECKING, cast, overload
  from warnings import warn
  import numpy
  import pandas
  from pandas.core.groupby import DataFrameGroupBy
  from ..exceptions import PlotnineError, PlotnineWarning
  from ..mapping import aes
label_desc: Use image node_id 7 for calling a global function with example usage: add_margins(df, vars, margins) and returns: merged, df