code: def _pairwise_grid(data_dict: dict) -> pd.DataFrame:
      """Creates a pairwise grid (cartesian product) of data by using the
      key-values of the dictionary.
  
      Parameters
      ----------
      data_dict : dict
          A dictionary containing the covariates as keys and their values as the
          values.
  
      Returns
      -------
      pd.DataFrame
          A dataframe containing values used as input to the fitted Bambi model to
          generate predictions.
      """
      keys, values = zip(*data_dict.items())
      cross_joined_data = pd.DataFrame(
          [dict(zip(keys, v)) for v in itertools.product(*values)]
      )
      return cross_joined_data
  
file_path: bambi/bambi/interpret/create_data.py
imports: import itertools
  from typing import Union
  from statistics import mode
  import numpy
  import pandas
  from pandas.api.types import is_categorical_dtype, is_float_dtype, is_integer_dtype, is_numeric_dtype, is_object_dtype, is_string_dtype
  from bambi import Model
  from bambi.interpret.utils import ConditionalInfo, enforce_dtypes, get_model_covariates, VariableInfo
  from bambi.interpret.logs import log_interpret_defaults
label_desc: Use image node_id 2 for calling a global function with example usage: _pairwise_grid(data_dict) and returns: cross_joined_data