功能介绍

把数据中的缺失值补上

参数说明

名称 中文名称 描述 类型 是否必须？ 默认值
outputCols 输出结果列列名数组 输出结果列列名数组，可选，默认null String[] null

脚本示例

  1. data = np.array([
  2.             ["a", 10.0, 100],
  3.             ["b", -2.5, 9],
  4.             ["c", 100.2, 1],
  5.             ["d", -99.9, 100],
  6.             ["a", 1.4, 1],
  7.             ["b", -2.2, 9],
  8.             ["c", 100.9, 1],
  9.             [None, None, None]
  10. ])
  12. colnames = ["col1", "col2", "col3"]
  13. selectedColNames = ["col2", "col3"]
  15. df = pd.DataFrame({"col1": data[:, 0], "col2": data[:, 1], "col3": data[:, 2]})
  16. inOp = dataframeToOperator(df, schemaStr='col1 string, col2 double, col3 long', op_type='batch')
  19. # train
  20. trainOp = ImputerTrainBatchOp()\
  21.            .setSelectedCols(selectedColNames)
  23. trainOp.linkFrom(inOp)
  25. # batch predict
  26. predictOp =  ImputerPredictBatchOp()
  27. predictOp.linkFrom(trainOp, inOp).print()
  29. # stream predict
  30. sinOp = dataframeToOperator(df, schemaStr='col1 string, col2 double, col3 long', op_type='stream')
  32. predictStreamOp = MaxAbsScalerPredictStreamOp(trainOp)
  33. predictStreamOp.linkFrom(sinOp).print()
  36. StreamOperator.execute()

脚本运行结果

  1.  col1        col2  col3
  2. 0     a   10.000000   100
  3. 1     b   -2.500000     9
  4. 2     c  100.200000     1
  5. 3     d  -99.900000   100
  6. 4     a    1.400000     1
  7. 5     b   -2.200000     9
  8. 6     c  100.900000     1
  9. 7  None   15.414286    31