code: def expr_reducers():
      data = [
          [random.uniform(-10000, 10000) for r in range(10)]
          for c in range(10)
      ]
      h2o_data_1 = h2o.H2OFrame(data)
      np_data = np.array(data)
      row, col = h2o_data_1.dim
      h2o_data = h2o_data_1 + 2
      np_data = np_data + 2
  
      def check_values(h2o_data, numpy_data):
          success = True
          for i in range(10):
              r = random.randint(0, row - 1)
              c = random.randint(0, col - 1)
              h2o_val = h2o_data[r, c]
              num_val = numpy_data[r, c]
              if not abs(h2o_val - num_val) < 1e-06:
                  success = False
                  print(
                      "check unsuccessful! h2o computed {0} and numpy computed {1}".format(
                          h2o_val, num_val
                      )
                  )
          return success
  
      h2o_val = h2o_data.min()
      num_val = np.min(np_data)
      assert abs(h2o_val - num_val) < 1e-06, (
          "check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and "
          "numpy".format(h2o_val, num_val)
      )
      h2o_val = h2o_data.max()
      num_val = np.max(np_data)
      assert abs(h2o_val - num_val) < 1e-06, (
          "check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and "
          "numpy".format(h2o_val, num_val)
      )
      h2o_val = h2o_data.sum().sum(axis=1)[:, 0]
      num_val = np.sum(np_data)
      assert abs(h2o_val - num_val) < 1e-06, (
          "check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and "
          "numpy".format(h2o_val, num_val)
      )
      pyunit_utils.np_comparison_check(
          h2o_data.var(), np.cov(np_data, rowvar=0, ddof=1), 10
      ), "expected equal var values between h2o and numpy"
  
imports: from builtins import zip
  from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  import numpy
  import random
label_desc: Use image node_id 1 for calling a global function with example usage: expr_reducers() and returns: success