code: def from_arrays(cls, arrays, sortorder=None, names=None):
          
          error_msg = "Input must be a list / sequence of array-likes."
          if not is_list_like(arrays):
              raise TypeError(error_msg)
          elif is_iterator(arrays):
              arrays = list(arrays)
  
          # Check if elements of array are list-like
          for array in arrays:
              if not is_list_like(array):
                  raise TypeError(error_msg)
  
          # Check if lengths of all arrays are equal or not,
          # raise ValueError, if not
          for i in range(1, len(arrays)):
              if len(arrays[i]) != len(arrays[i - 1]):
                  raise ValueError('all arrays must be same length')
  
          from pandas.core.arrays.categorical import _factorize_from_iterables
  
          codes, levels = _factorize_from_iterables(arrays)
          if names is None:
              names = [getattr(arr, "name", None) for arr in arrays]
  
          return MultiIndex(levels=levels, codes=codes, sortorder=sortorder,
                            names=names, verify_integrity=False)
docs: Convert arrays to MultiIndex.
  
          Parameters
          ----------
          arrays : list / sequence of array-likes
              Each array-like gives one level's value for each data point.
              len(arrays) is the number of levels.
          sortorder : int or None
              Level of sortedness (must be lexicographically sorted by that
              level).
          names : list / sequence of str, optional
              Names for the levels in the index.
  
          Returns
          -------
          index : MultiIndex
  
          See Also
          --------
          MultiIndex.from_tuples : Convert list of tuples to MultiIndex.
          MultiIndex.from_product : Make a MultiIndex from cartesian product
                                    of iterables.
          MultiIndex.from_frame : Make a MultiIndex from a DataFrame.
  
          Examples
          --------
          >>> arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']]
          >>> pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
          MultiIndex(levels=[[1, 2], ['blue', 'red']],
                     codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
                     names=['number', 'color'])