code: def sum_of_squared_diffs_from_mean(
      self,
      on: str,
      ignore_nulls: bool,
      mean: Optional[U] = None,
  ) -> Optional[U]:
      import pyarrow.compute as pac
  
      if mean is None:
          # If precomputed mean not given, we compute it ourselves.
          mean = self.mean(on, ignore_nulls)
          if mean is None:
              return None
      return self._apply_arrow_compute(
          lambda col, skip_nulls: pac.sum(
              pac.power(pac.subtract(col, mean), 2),
              skip_nulls=skip_nulls,
          ),
          on,
          ignore_nulls,
      )
  
imports: import collections
  import heapq
  import random
  from typing import TYPE_CHECKING, Any, Callable, Dict, Iterator, List, Optional, Tuple, TypeVar, Union
  import numpy
  from ray._private.utils import _get_pyarrow_version
  from ray.air.constants import TENSOR_COLUMN_NAME
  from ray.data._internal.arrow_ops import transform_polars, transform_pyarrow
  from ray.data._internal.numpy_support import convert_udf_returns_to_numpy, is_valid_udf_return
  from ray.data._internal.table_block import TableBlockAccessor, TableBlockBuilder
  from ray.data._internal.util import _truncated_repr, find_partitions
  from ray.data.block import Block, BlockAccessor, BlockExecStats, BlockMetadata, KeyType, U
  from ray.data.context import DataContext
  from ray.data.row import TableRow
label_desc: Use image node_id 27 for calling the ArrowBlockAccessor obj's underlying member method code with example usage: obj.sum_of_squared_diffs_from_mean(on, ignore_nulls, mean) and returns: self, None