parameters: (data, columns, coerce_float=False, dtype=None)
return_statement: return _convert_object_array(
          content, columns, dtype=dtype, coerce_float=coerce_float
      )
docstring: Convert list of dicts to numpy arrays
  
      if `columns` is not passed, column names are inferred from the records
      - for OrderedDict and dicts, the column names match
        the key insertion-order from the first record to the last.
      - For other kinds of dict-likes, the keys are lexically sorted.
  
      Parameters
      ----------
      data : iterable
          collection of records (OrderedDict, dict)
      columns: iterables or None
      coerce_float : bool
      dtype : np.dtype
  
      Returns
      -------
      tuple
          arrays, columns
docstring_summary: Convert list of dicts to numpy arrays
docstring_tokens: Convert list of dicts to numpy arrays
function: def _list_of_dict_to_arrays(data, columns, coerce_float=False, dtype=None):
      """Convert list of dicts to numpy arrays
  
      if `columns` is not passed, column names are inferred from the records
      - for OrderedDict and dicts, the column names match
        the key insertion-order from the first record to the last.
      - For other kinds of dict-likes, the keys are lexically sorted.
  
      Parameters
      ----------
      data : iterable
          collection of records (OrderedDict, dict)
      columns: iterables or None
      coerce_float : bool
      dtype : np.dtype
  
      Returns
      -------
      tuple
          arrays, columns
      """
  
      if columns is None:
          gen = (list(x.keys()) for x in data)
          sort = not any(isinstance(d, dict) for d in data)
          columns = lib.fast_unique_multiple_list_gen(gen, sort=sort)
  
      # assure that they are of the base dict class and not of derived
      # classes
      data = [(type(d) is dict) and d or dict(d) for d in data]
  
      content = list(lib.dicts_to_array(data, list(columns)).T)
      return _convert_object_array(
          content, columns, dtype=dtype, coerce_float=coerce_float
      )
function_tokens: def _list_of_dict_to_arrays ( data , columns , coerce_float = False , dtype = None ) : if columns is None : gen = ( list ( x . keys ( ) ) for x in data ) sort = not any ( isinstance ( d , dict ) for d in data ) columns = lib . fast_unique_multiple_list_gen ( gen , sort = sort ) # assure that they are of the base dict class and not of derived # classes data = [ ( type ( d ) is dict ) and d or dict ( d ) for d in data ] content = list ( lib . dicts_to_array ( data , list ( columns ) ) . T ) return _convert_object_array ( content , columns , dtype = dtype , coerce_float = coerce_float )