code: def stats_variance_1d(data, ddof=0):
      a_a, b_b = 0, 0
      for i in data:
          a_a = a_a + i
          b_b = b_b + i * i
      var = b_b / (len(data)) - ((a_a / (len(data))) ** 2)
      var = var * (len(data) / (len(data) - ddof))
      return var
  
imports: import warnings
  from collections.abc import Sequence
  from copy import copy
  from copy import deepcopy
  import numpy
  import pandas
  from scipy.fftpack import next_fast_len
  from scipy.interpolate import CubicSpline
  from scipy.stats.mstats import mquantiles
  from xarray import apply_ufunc
  from ..None import _log
  from ..utils import conditional_jit, conditional_vect, conditional_dask
  from .density_utils import histogram
label_desc: Use image node_id 10 for calling a global function with example usage: stats_variance_1d(data, ddof) and returns: var