class_docstr: This class replaces each missing value with the average of all the last
  window_size (default=10) values.
  
  (If the first values are missing, they are replaced by the closest non
  missing value.)
class_docstr_tok: ["This","class","replaces","each","missing","value","with","the","average","of","all","the","last","window_size","(","default=10",")","values",".","(","If","the","first","values","are","missing",",","they","are","replaced","by","the","closest","non","missing","value",".",")"]
code: def __init__(self, window_size: int = 10) -> None:
      self.window_size = 1 if window_size < 1 else window_size
  
imports: from typing import List, Optional, Union, Type
  import numpy
  import pandas
  from gluonts.core.component import validated
  from gluonts.dataset.common import DataEntry
  from gluonts.dataset.field_names import FieldName
  from gluonts.time_feature import TimeFeature
  from ._base import MapTransformation, SimpleTransformation
label_desc: Use image node_id 1 to create a new RollingMeanValueImputation object from inherited base classes: MissingValueImputation with example: obj = RollingMeanValueImputation(window_size)